She Talks Tech podcast, Working with Data in Financial Services' with Shafreen Sayyed & Sara Mitchell, AWS 1

Listen to our latest She Talks Tech podcast on 'Working with Data in Financial Services' with Shafreen Sayyed & Sara Mitchell, AWS

She Talks Tech podcast, Working with Data in Financial Services' with Shafreen Sayyed & Sara Mitchell, AWS 1

This episode is the second of an AWS special series of the She Talks Tech podcast.

The objective of these podcasts is to demonstrate how Cloud technology is helping transform many industries like Retail, Financial Services or even Sports. But we also want to hear from the women behind these stories who are enabling these transformations to understand what they do day to day and how they got into working in technology.

In this episode, Shafreen, Senior Solutions Architect, AWS and Sara, Senior Manager, AWS, will share you their story about “Working with Data in Financial Services”.

LISTEN HERE

‘She Talks Tech’ brings you stories, lessons and tips from some of the most inspirational women (and men!) in tech.

From robotics and drones, to fintech, neurodiversity and coronavirus apps; these incredible speakers are opening up to give us the latest information on tech in 2021.

Vanessa Valleley OBE, founder of WeAreTheCity and WeAreTechWomen brings you this latest resource to help you rise to the top of the tech industry. Women in tech make up just 17 per cent of the industry in the UK and we want to inspire that to change.

WeAreTechWomen are delighted to bring this very inspiring first series to wherever you normally listen to podcasts!

So subscribe, rate the podcast and give it a 5-star review – and keep listening every Wednesday morning for a new episode of ‘She Talks Tech’.

Produced by Pineapple Audio Production.

Discover more from our
She Talks Tech podcast

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Listen to our latest She Talks Tech podcast on 'The Future of Data: Protecting Data in a Global Economy' with Deborah O'Neill, Oliver Wyman

She Talks Tech podcast - Deborah O'Neill, Oliver Wyman 2

Today we hear from Deborah O’Neill, the Head of Digital for UK and Ireland and a partner at Oliver Wyman.

In this episode of She Talks Tech, Deborah explores how countries across the globe are asking crucial questions that will shape our future, including, whether free flow of data will persist, how to trust information we’re presented online and what we can do to protect our privacy rights.

Alongside the latest Oliver Wyman Forum research, Deborah helps make sense of the complex intersection between data, trust and the access to services we increasingly take for granted.

If you want to find out more about Deborah – you can connect with her on LinkedIn or visit www.oliverwyman.com.

LISTEN HERE

‘She Talks Tech’ brings you stories, lessons and tips from some of the most inspirational women (and men!) in tech.

From robotics and drones, to fintech, neurodiversity and coronavirus apps; these incredible speakers are opening up to give us the latest information on tech in 2021.

Vanessa Valleley OBE, founder of WeAreTheCity and WeAreTechWomen brings you this latest resource to help you rise to the top of the tech industry. Women in tech make up just 17 per cent of the industry in the UK and we want to inspire that to change.

WeAreTechWomen are delighted to bring this very inspiring first series to wherever you normally listen to podcasts!

So subscribe, rate the podcast and give it a 5-star review – and keep listening every Wednesday morning for a new episode of ‘She Talks Tech’.

Produced by Pineapple Audio Production.

Discover more from our
She Talks Tech podcast

LISTEN HERE

assorted numbers on a board, women in data

Working with numbers | Women in Data

assorted numbers on a board, women in data

When Lyndsey Swann needed a career reboot, she studied for an HND in computing at night school and this led to her first role in data. Lyndsey now heads up ‘customer excellence’ for Gazprom Energy - a role all about maximising and monetising data and insight across the organisation. Lyndsey tells us why she thinks women are underrepresented in the data sector and what can be done about it.

The percentage of roles linked to data science being taken by women has dropped from 41 per cent in 2005, to 34 per cent in 2009, and to 27 per cent in 2019.

Despite millions of pounds being spent to encourage greater diversity in STEM careers, worryingly, jobs involving data are neither attracting, nor being secured by, female candidates.

I love working with data because it enables better business decisions. It often takes the emotion or guesswork out of decision making and will ultimately improve an organisation’s performance by enhancing service to the customer and increasing revenue to the business. It’s fantastic to create a compelling story through data that makes people think differently and introduces them to new ideas. Data can surprise, prove wrong or validate original thought – you never know what you are going to find.

The unconscious message

But clearly data isn’t the career choice for many women. I think this is due to the choices young girls make at school, as well as the unconscious messages they are given. For a large part, data analytics and data science doesn’t inspire young girls. While many enjoy maths and sciences at primary school, interest wanes when they move into senior school and become teenagers - where many conform with ‘the norm’.

The way data science is ‘sold’ in many schools is also partly to blame. Even today people assume that girls’ minds are less technical and not as logical. Although this is unconscious in many cases, it puts girls off studying these subjects due to the fear of failure. This perpetuates the vicious cycle of lacking female role models that could then inspire the female data scientists of the future.

So how can we improve the situation? Firstly, we must engage young girls when they are in high school and making those crucial GCSE choices. It needs to be made clear that a career in data is a rewarding, achievable and sustainable career choice. Bringing women in data into high schools to inspire others would help.

Secondly, a clearer career roadmap would be useful. Data science is not the only role available to those who are inspired by analytics. There are also areas like customer insight, or research and marketing roles that all utilise data and would benefit hugely from greater diversity.

Broadening the spectrum

This diversity would bring tangible benefits and improvements to industry; for example, a broader spectrum of views and different approaches to solving business problems. Women tend to excel in problem solving, agility of thought, and communications – all crucial attributes in my line of work.

I also think women are generally strong at logical decision making, are highly action-orientated and active listeners. These are essential attributes in data analytics & data science, especially when it comes to asking the right questions of the data and insight to monetise the outcomes as constantly demanded in business today.

However, we should be aiming for a place where gender is irrelevant and the most talented people should grow and thrive equally in the data sector, regardless of this. As in many areas, this requires substantial effort to remove unconscious bias.

Making a difference

Another way the sector can nurture more talent, including women, is by demonstrating the connected worlds that data science is part of. My career transcends two very different but connected worlds – deep data insights and customer experience. Connections like these are important because they highlight the wider impact that working with data has. It’s not just about being into numbers. It’s what you learn from them and how you can make a difference.

These ‘data connections’ should encourage more people who are data literate but also enjoy creative thinking and problem solving, to look further at data analytics & data science as a rewarding career path. The industry needs the right combination of technical data science and programming skills but also the ability to utilise that insight for commercial gain.

Now that so many customer interactions are digital, there are new opportunities for younger candidates to shine earlier. They can quickly dominate the field in new data areas such as web analytics, social media listening, sentiment analysis, and AI.

My own journey

I’m both proud and lucky to work for a business today that takes diversity seriously. It’s this attitude and the people within Gazprom Energy that sets it apart from other B2B utilities suppliers. Within the UK we have a balanced senior team in terms of outlook, gender, and specialism, which makes for fair leadership and a strong foundation for the business.

The skillset I need in my customer excellence team is widespread, from research professionals and process specialists, to customer insight analysts and CRM experts. This should ensure diversity. First and foremost, I want to recruit people that are passionate about creating best in class customer experience using data, insight, research, and technology, so we are continually able to grow and innovate.

Gender will not be the primary factor in choice of recruits; however, I strongly hope that I can build a diverse team that benefits from great female candidates in the mix.

Lyndsey SwannAbout the author

Lyndsey Swann is Head of Customer Excellence at Gazprom Energy.

With over 15 years’ experience in in customer insight and analytics, research, strategy development, segmentation, customer experience, CRM and customer services, Swann works to put the customer at the heart of decision making whether that be B2C or B2B.


If you are a job seeker or someone looking to boost their career, then WeAreTechWomen has thousands of free career-related articles. From interview tips, CV advice to training and working from home, you can find all our career advice articles here.


She Talks Tech podcast episode - Data and Trust Beyond COVID-19 - Deborah O'Neill

Listen to our latest She Talks Tech podcast episode on 'Data and Trust Beyond COVID-19' with Deborah O'Neill

She Talks Tech podcast episode - Data and Trust Beyond COVID-19 - Deborah O'Neill

Today we hear from Deborah O’Neill – the UK head of Digital and a partner at Oliver Wyman, where she leads complex digital transformations at the world’s largest companies. 

As the UK looks to further contain COVID-19 through app-based contact tracing, we look at the public’s attitudes towards sharing personal data and how it is evolving.

Deborah will dissect what drives trust and explore whether it is possible to increase the degree to which people in the UK will engage with data sharing and contact tracing.

You can find out more about and connect with Deborah on Twitter at @DeborahLabsOW

LISTEN HERE


‘She Talks Tech’ brings you stories, lessons and tips from some of the most inspirational women (and men!) in tech.

From robotics and drones, to fintech, neurodiversity and coronavirus apps; these incredible speakers are opening up to give us the latest information on tech in 2020.

Vanessa Valleley OBE, founder of WeAreTheCity and WeAreTechWomen brings you this latest resource to help you rise to the top of the tech industry. Women in tech make up just 17 per cent of the industry in the UK and we want to inspire that to change.

WeAreTechWomen are delighted to bring this very inspiring first series to wherever you normally listen to podcasts – and the first three episodes are now live!

So subscribe, rate the podcast and give it a 5-star review – and keep listening every Wednesday morning for a new episode of ‘She Talks Tech’.

Produced by Pineapple Audio Production.


data, coding

Data driven innovation: why the marketing team must be the custodians of consumer privacy  

data, coding

Shallu Behar-Sheehan, Chief Marketing Officer at Trūata

Data privacy has never been a more important issue for consumers. The COVID-19 pandemic has thrust the topic into the spotlight, with constant questions over track and trace practices, and confusion about collecting and storing citizen data.

Globally, the evolving privacy laws now dictate how and why brands must protect today’s consumer when it comes to personal data. Brands increasingly know more about their audiences through their digital appetite, often without ever meeting them. However, finding a way to make sense of, and utilise, the data that can be collected through their customers’ digital footprints, while adhering to laws and regulations, has become a big challenge.

For example, Spotify is known as a music streaming service which has now developed into a successful model for collecting vast amounts of consumer data based on their preferences. This helps Spotify to drive business decisions as well as create unique and tailored experiences for an audience of more than 180 million users, including 83 million subscribers across 65 markets. This business model is a blueprint, both for cloud-native companies and established enterprises, and highlights how, transactional personal data is one of the world’s most valuable assets.

Balancing monetisation and trust

The balance between data privacy, data monetisation and consumer trust is a complex one to find. It can be challenging to understand exactly where the responsibility lies for ensuring that the personal data collected by a business is kept private.

Consumers desire a personal relationship with brands and a customised experience (driven primarily by their own data), but at the same time, don’t want to risk their data being mishandled or misappropriated. In fact, our recent Global Consumer State of Mind Report has revealed that 61% of global consumers said they would stop using brands if they ‘stalked’ them online with too many personalised offers. They want the unique experience they desire but not at the expense of their privacy, and 77% believe they should own their ‘digital selves’.

The main issue is consumers aren’t really sure where their data is going or what is being done with it. Consequently, we’re seeing a disconnect between the brand and its consumer. When consumers don’t understand the consent they give, the shortcomings of the techniques being used to ‘anonymize’ their data aren’t always evident. All too often customers have become accustomed to clicking past mechanics such as privacy notices, without really making a proactive, and more importantly, informed choice about sharing very personal and private information?

It’s not that the public don’t care about their data as recent research has revealed that 65% of consumers are concerned with the way their data is collected. What they expect is peace of mind that a level of ‘digital trust’ has been built – and this is currently where there is a disconnect. Our report shows that if trust isn’t established with a brand, 77% of consumers would take their own steps to reduce their digital footprint. However, brands that behave ethically and transparently with data will be able to win this trust, with 66% of people  being more likely to be loyal to a brand if they trust them to use their personal data appropriately.

Issues over data responsibility

One of the key problems that surrounds the use of personal data is responsibility – responsibility for whose role it is to educate the public on exactly how their data is being collected. While some brands may say the right things in principle, they are less forthcoming in detail which can only create confusion and more distrust.

When vague and trite mantras are all that is being offered, consumers find it hard to trust the organisations they are dealing with. In fact,  62%  state they will continue to use companies who are open when explaining what they do with the data they hold. However, with many brands and companies shying away from doing this, consumers have little choice but to carry on being wary - even to the point of avoiding brands where they can’t easily verify the reputation for privacy.

Who should be held responsible?

The responsibility for data protection and compliance is often given to IT, legal or privacy teams, even though they are not front of house and rarely interact with consumers. Therefore, traditionally these teams are not viewed as impacting or being responsible for brand value. The problem worsens if the team with responsibility for data protection has little interaction with the marketing team who are responsible for delivering the brand experience.

While brands need data to understand more about their consumers, ensuring privacy and transparency are key considerations for building and maintaining loyalty. Marketers can’t build lasting, reciprocal relationships, and consequently, can’t build meaningful predictive datasets without that loyalty and trust.

When marketers take the reins and use their position to educate and communicate clearly and confidently with consumers about their brand’s adherence to data protection laws, consumers will regain confidence in the brand’s commitment to data privacy best practice. Ensuring consumers feel comfortable with the way their data is being used will make it easier for brands to collect more data in the future in order to achieve valuable insights. Consumers must be sure that third parties do not have access to their data and that it is protected from being exploited or sold for commercial gain without their agreement.

Data privacy: the heart of brand management DNA

Marketers must take the lead role in planning, strategising and guiding the responsible use of data within their organisations and champion a privacy-centric consumer experience. Given they are on the frontline, CMOs must instigate collaboration with CIOs and CDOs, to ensure privacy considerations are deeply embedded into business strategies. This will ensure all are aligned in consumer trust and delivering a model that puts privacy first. In a world where brands increasingly rely on data to innovate and grow, trust and data privacy are too important for marketers to ignore when brand reputation can so easily be damaged beyond repair.

So, what do marketers need to know?

Data privacy and transparency are crucial in the new trust economy

Understandably, consumers want to keep their personal data private. If brands can assure them of this, then they are likely to be more successful. In fact, 64% of global consumers agree they would engage with brands that make it easy for them to control how their data is used. Today, trust is regarded as a highly valuable currency with transparency being a key factor in how consumers interact with brands. Without an understanding of the trust economy, businesses simply will not survive.

Another recent study shows that GDPR-compliant companies outperform their competition across a range of metrics. Thus, the ability to assure consumers of data privacy can provide a commercial advantage, with transparency winning hearts and minds. By embracing privacy-enhancing practices and technologies, such as anonymization, brands will stand to profit. However, this must be done in the right way, otherwise they risk it backfiring and harming the company’s reputation.

Many companies say they anonymize consumer data in order to comply with GDPR and similar data protection laws, but recent academic research demonstrated how easy it is to re-identify an individual from a so-called “anonymized” dataset. The frequent misuse of the term ‘anonymization’ is something both companies and consumers should be aware of. A better and more robust approach would be to have a separate expert organisation independently carry out the anonymization and only release aggregate insights.

The value of genuine data privacy

Marketers know the value of data that is securely anonymized. As they interact with consumers more than IT or legal teams, they understand this better than anyone else in the company. Marketers recognise that only rigorous, proven, data anonymization lets them build long-term digital trust with consumers. They are also aware of the “digital creep” label that is associated with brands who misuse consumer data to deliver a personalised experience. This is likely to turn consumers away from their brands, our research shows that 45% of consumers say data tracking for personalisation is invasive, 32% even go as far to say it’s creepy, and 24% say sinister.

As marketers have this understanding and can relate with consumer desires, they need to establish a reciprocal relationship with them. A ‘you trust us with your data, and we’ll not only look after it, but provide you with a valued tailored experience’ model. Building this relationship on privacy-enhanced analytics, will highlight the value of the marketing team to the business, ensuring they remain integral to the growth and vision of the organisation. We know that data is such a powerful commodity, and it’s now time for organisations to put data privacy matters into the hands of marketers and empower them to be the true custodians of their consumers’ privacy, and the overall brand experience.

About the author

Shallu Behar-SheehanShallu Behar-Sheehan is an accomplished international marketer with over 25 years’ experience in creating and delivering integrated strategic revenue generating marketing initiatives across the UK, Europe, Middle East, Africa, and Russia (EMEAR), North America and Asia Pacific (APAC). Acknowledged as one of the Top 20 Women in Tech by B2B Marketing and one of the 100 Most Influential B2B Technology Marketers in Europe by the prominent online tech community Hot Topics, Shallu has helped technology organisations significantly raise their brand profile in highly competitive environments. As an innovative and award winning leader, Shallu has proven team management skills and a strong track record of spearheading industry leading campaigns against aggressive business targets, which deliver timely and impactful returns on investment.


If you are a job seeker or someone looking to boost their career, then WeAreTechWomen has thousands of free career-related articles. From interview tips, CV advice to training and working from home, you can find all our career advice articles here


female data scientist, woman leading team

Making a difference in the world: navigating a career in data and analytics

By Sophie Hiscock, Graduate Consulting Analyst at TrueCue

female data scientist, woman leading teamWhile the technology industry is forward thinking in terms of its efforts to support the ‘new normal’ – becoming a force for good in many ways at this time – it still has a way to go in terms of actively encouraging women to explore a career in technology.

Recent research by PwC, carried out across A-Level and university students, found that only 27% of female students would consider a career in technology, compared to 61% of males, with the main reason being the lack of information, advice and role models for women.

To help bridge the gender diversity gap, it is critical – particularly at a time when students are considering their future – that misconceptions around women working in technology are resolved.

In light of this, I want to share my personal experience of working in technology, how I navigated a path in the data analytics industry as a Philosophy and Economics graduate and ultimately how analytics enable us to make a positive difference to the world.

Entering the technology industry

Studying Philosophy and Economics at university inspired me to pursue a career in data and analytics as both subjects demand rigorous thinking and the ability to apply theory to real-world problems, skills that are central to anyone who works with data in business contexts.

That being said, the technology industry is increasingly diverse in terms of the academic and professional backgrounds of employees. If you do not have academic experience that specifically relates to technology, do not worry. As long as you have an interest in analytics and an aptitude for numbers, you will quickly be able to grow in this sector. A formal background in Maths and Data Science is helpful, but these skills can easily be learnt independently.

Attending bootcamps and online courses can be a great way of understanding whether the technology industry is for you. When I was at university, I enrolled in a programme called ‘Code First Girls’ – a bootcamp taught by women with careers in technology, offering free coding lessons in Python among other languages. Many of the female teachers I came across did not come from STEM backgrounds and speaking to them helped me realise the range of work available to me.

In this way, having female role models is another critical factor in increasing the number of women looking to get into technology. I was lucky to have met some amazing women throughout my university courses and internships. If you are stuck for people to answer your questions at this socially distanced time, I would suggest reaching out to industry experts via platforms such as LinkedIn or LeanFurther which connects young women with professionals in different industries.

Looking beyond the stereotypes

There are vast misconceptions about what working in technology actually involves. When I first started at TrueCue I quickly learnt that working in data is not always about the technical side, being able to communicate well both with the client directly and through visualisations is central.

This balance is reflected in what I do on a daily basis. For example, a typical project for me will begin with requirements gathering, data scoping, data preparation and analysis and will culminate in a visual presentation of the data through a series of dashboards that clients can interact with. Having both the sensitivity and technological experience to fully understand and help the client are key components of working in data and analytics.

Since my time at TrueCue I have worked on many ‘tech for good’ projects, including one with a company operating in the pharmaceutical industry. On this project, I designed an app to help doctors and nurses working in different healthcare facilities to plan for the uptake of a particular drug. This app ensured doctors would be able to plan out resourcing, while taking into account the rate at which patients tend to miss appointments. Speaking directly with stakeholders working in hospitals helped me appreciate how – beyond improving business performance – the work I was doing could improve people’s lives.

Breaking down the barriers

The technology industry is constantly finding new ways to improve people’s lives and with companies becoming increasingly outspoken about the need for greater diversity, we should look forward to more improvements in the future.

To become “Women in Data”, girls and young women must be provided with more information about the amazing work available to them and already done by women in the tech industry. On top of this, a variety of resources are publicly available that everyone, regardless of their academic background, can take advantage of to improve their skillsets and open up more career opportunities.

Technology is open to everyone, no matter their gender, skin colour or background and we must do all we can to elevate this message. To play our part in this at TrueCue we are running a campaign to provide hands-on experience, advice and resources to women considering careers in the industry. Our first event will be a Hackathon on a COVID-19 dataset where participants will have the chance to grow their skills and meet others interested in analytics – please stay tuned to our social media channels for further information.


If you are a job seeker or someone looking to boost their career, then WeAreTechWomen has thousands of free career-related articles. From interview tips, CV advice to training and working from home, you can find all our career advice articles here


Cloud computing featured

Data and computers don’t care about gender – and neither does the cloud!

Cloud computing

Article provided by Lori MacVittie, Principal Threat Evangelist, F5 Networks

Although 2019 was a landmark year for women in tech, with government data revealing over one million women in the UK now work in STEM-related sectors, there is no room for complacency.

As a proportion of the tech workforce, women make up a meagre 16 per cent – a stat that hasn’t moved in the last decade. In fact, in 2019 it dropped 1,500 places from the previous year.

While the wheels are in motion to facilitate greater tech diversity across the world (with varying levels of success), there are still misconceptions about the industry’s ability to support female talent and produce role models in leadership positions. Everyone needs to do more to change that, particularly as we face worldwide shortages in disciplines like security and cloud computing.

Beating the bias

I’m lucky that I come from the Midwest of the US. The area is full of insurance companies and programming jobs with strong female representation. This includes my own mother, who worked as a programmer in the 70s. It just seemed to be part of our culture to have women in these kinds of positions. Fortunately, I haven’t come across many substantial career roadblocks based on my gender.

That being said, like so many other women, I’ve experienced gender-driven bias throughout my career. I’ve dealt with long-standing, ubiquitous issues. This includes male colleagues who won’t take direction from a woman, and dealing with people being taken aback when they realise – lo and behold – that I, and other women in the industry, actually know what we’re talking about! It’s not unusual after speaking at an event to be approached by people who are shocked at my ability to deliver an educational and insightful talk.

We can’t let bias bring us down or stop us from working to achieve our goals. It’s something we must overcome together as an industry, and as a society.

Welcome to the cloud!

It’s important to remember that tech is the fastest-growing industry and there are so many areas within the sector where women can flourish – some more easily than others.

For example, cloud computing has boomed in the last decade. Coincidental or not, its rise was accompanied by a significant drive to support women ‘in cloud’. In fact, cloud as a technology is often credited for democratising the resources needed for women to become entrepreneurs. Anecdotally, I think that the cloud industry has definitely been less challenging to establish credibility in than other technological industries.

That being said, I don’t see the range of opportunities being any different, except within the start-up space. Here, for example, cloud can make it easier to drive an idea to fruition, thanks to the wide range of options it offers. In fact, we’ve seen a recent explosion of women-led start-ups based in (and on) the cloud because of this.

The adoption of cloud-based solutions in the workplace has also meant that it’s easier to balance work and life. The tools you need to work with are accessible from anywhere, even at home. This alone can alleviate stress on women who struggle with work-life balance.

Wherever you go in tech, in the current climate, it’s likely that you’ll end up in a male-dominated environment. If that makes you uncomfortable, then that’s OK. Help and support is there. Make sure you find a mentor early on, or friend who you can share experiences with and lean on. In addition, it is useful to find a business or educational body that will provide the right support to help you lead a successful career.

As an industry, it’s also important that we address a widespread tendency to dismiss women in technology that aren’t in a hands-on role. We need to support and promote all women – irrespective of job title or function.

Whoever you are, whatever you wear, or whatever personality you have, is irrelevant. There’s a role for you in tech. Be bold, be yourself and don’t be put off. If we want change, we need to be the forerunners!

Lori MacVittieAbout the author

Lori MacVittie has been working at F5 for just under 14 years. Having started out as a marketing manager, she has worked her way up to becoming Principal Technical Evangelist in the Office of the CTO.

During her career, Lori has been an application developer, system engineer, consultant, writer, author, strategist, and evangelist. Her specialities include: application development, application integration, application infrastructure, application delivery, application security, cloud, SDN, and DevOps.


If you are a job seeker or someone looking to boost their career, then WeAreTechWomen has thousands of free career-related articles. From interview tips, CV advice to training and working from home, you can find all our career advice articles here.


female data scientist, woman leading team

Data is the new oil - how to break through a male-dominated industry

By Dr. Zeinab Bakhtiarinoodeh, Senior Data Scientist at TomTom

female data scientist, woman leading teamBe brave. Don’t be afraid to ask for more. Don’t be afraid to make mistakes. Practice at building your confidence. And work hard.

Those are the lessons that I’d give any women starting their career in the STEM industry. Too often we devalue the skills we have, and don’t recognise what we bring to the workplace.

After all, Maryam Mirzakhani (winner of the Field Medal, the Nobel prize for Mathematics) graduated from my college. If she can do it, why can’t I?

There is no doubt that computer science is a male-dominated environment and there is no doubt that it can be intimidating. When doing my PhD studies in computer science and logic, I was the only female in a majority of settings I found myself in. I always thought I had to be exceptional to make it as a woman.

But that changed when I came to TomTom. When I turned up for my interview I was warmly welcomed, and truth be told, that can sometimes be hard to come by as a Muslim woman. From that moment, I knew that I would be able to grow in this company, both professionally and as a person.

Paying it forward

Yes, most CTOs are men, and in such a male-led industry, it can be daunting for women to break through. However, by putting more women in leadership roles at the top of their fields, we can provide mentorship and encourage younger women to pursue a career in tech.

I’ve been lucky to have a number of mentors at TomTom. My primary mentor ended up being my inspiration. She took me under her wing and showed me what’s possible.

From this experience, I was able to understand the importance of becoming a mentor myself. Following a talk I held on data science at CODAM (a tuition-free coding school in Amsterdam set up by TomTom’s co-founder, Corinne Vigreux), I was approached by a number of young aspiring students who wanted to explore mentorship with me.

I strongly believe that “paying it forward” is key to pushing our industry on to bigger and better things, and changing the status quo. If you’re in a position of power or authority, please don’t be afraid to give others a helping hand. If you’re just getting started in the STEM industry, seek out a mentor, and remember to give back when the time comes.

Doing what you love and making a difference

Data is the new oil and is shaping the future. Everything we do generates data. Even making a phone call generates data. We are at the start of an exciting journey when it comes to analysing and understanding what data can do to automate processes.

As a Senior Data Scientist at TomTom, my role is tailored around helping my colleagues make better decisions that are driven by data. Each time I’m faced with a new task, I genuinely feel a sense of excitement, with the view of being able to make a difference. From training to building infrastructure for data products, I’ve learned to be bold, creative, innovative and lead a team effectively – something that TomTom encourages in all women within the company.

Remember that technology is there to help solve problems, rather than create them. Once you find a problem that you’re passionate about, you’ll know you’re making a difference.

Garnering skills for STEM success

I initially had my head and heart set on a career as a professor or researcher, and studied for a PhD in Computer Science and Logic. But making the switch to the data science industry was one of my best moves. Now, with an array of qualifications and skills under my belt, I feel as though I’m making a real difference in the role I have at TomTom.

Here’s five things I’d like to share with any aspiring STEM female:

  1. Keep learning. Learn the latest skills and coding methods. Keep up with the latest trends in Artificial Intelligence and Machine Learning. Listen to podcasts. Watch webinars. Read and absorb.
  2. If you want to become a master at coding, but aren’t a master in Mathematics, don’t worry – being a creative problem solver will help you along your way.
  3. Spruce up your presentation and communications skills. This will come in handy when sharing your ideas and solutions.
  4. Show resilience and willingness. Take on a challenge and work on it until the end, and embody the boldness that we, as women, harness.
  5. Have the courage to try new things. Being flexible to pivot will allow you to explore your capabilities to the fullest.

Zeinab TomTomAbout the author

With a six year working background in Mathematics and Computer Science, Zeinab has been in a male dominated industry for the majority of her career. Alongside qualifications in Neural Networks and Deep Learning, Regularization, Optimization and Structuring Machine Learning, Zeinab also speaks English, French, Persian and Turkish.

Today, at TomTom, Zeinab leverages Computer Science, Machine Learning and Mathematical modelling to turn data into a story, a fascinating feature for the users of TomTom products. She is passionate about science and technology, with the aim of using both to make the world a better place to live.

 


If you are a job seeker or someone looking to boost their career, then WeAreTechWomen has thousands of free career-related articles. From interview tips, CV advice to training and working from home, you can find all our career advice articles here


Computer Programmer Algorithmic Literacy

Algorithmic literacy – tomorrow’s #1 skill everyone needs to learn

Computer Programmer Algorithmic LiteracyAlgorithms and decision support systems increasingly influence our choices.

They do this in a number of ways, primarily by using our past behavior and the revealed preferences of people similar to us to help filter our options. Take review platforms such as Yelp or Foursquare, for example. It’s nothing new that we follow the advice of our friends and visit the restaurant that most of them recommend. But the internet has made it orders of magnitudes easier to share and aggregate data such as reviews or recommendations. So even though we theoretically have many options, we typically end up choosing the restaurant on top of the list (and/or the one with the largest number of reviews, a new study found).

Soon the world will be dominated by algorithms which predict fairly accurately what we want, prefer and do next. The more data these algorithms gather, the better their predictions will become. It’s not science-fiction to suggest that in the near future, algorithms will know which of our mental (and emotional) buttons to press in order to make us believe, want, or do things. In itself, this is not necessarily bad – after all, we use these algorithms voluntarily because they offer us some kind of benefit. They take some load off our shoulders to sift through options and present us with the most suitable ones – or they present the pieces of information that we are most likely to latch on to.

However, it’s not hard to see that incentives may not be fully aligned: From the perspective of their owners, algorithms are tools to accomplish a goal – such as selling products, keeping our eyes glued on a website, or making us like or dislike a political candidate. In solving these goals algorithms serve us suggestions (such as nuggets of ‘news’ that are designed to stir outrage and polarization) that may not be in line with the goals we set for ourselves (being open-minded and weighing evidence of either side to form a balanced opinion). Our dependency on algorithms can make us subject to manipulation.

There’s need for self-regulation, ethical codices and government intervention to shield against fraud, manipulation and addiction.

But there’s also the need for algorithmic literacy — to enable children, teenagers, and adults to understand, reflect on and wisely interact with algorithms:

  1. Understand what algorithms are. Most algorithms we encounter in our daily life are ‘prediction machines’: They are models that use existing data to predict missing data. For example, Spotify (or Pandora, or Apple Music) will take the songs you have listened to in the past (existing data) to predict what you will enjoy going forward (missing data). Importantly, algorithms only establish correlations between two items – not necessarily causations.
  2. Know where algorithms are deployed – today and in the future. In many cases, algorithms are both better (higher accuracy) and cheaper than humans to accomplish prediction tasks. This is especially true in environments that offer a lot of structured data, fairly consistent patterns and only a limited number of possible outcomes. For example, it’s comparatively easy for Google Maps to predict how crowded a restaurant will be at a given time, but quite difficult to forecast rare events such as earthquakes.
  3. Understand the intent/goals of those owning or deploying the algorithm. Algorithms are used to solve a particular problem, and their economics help understand the motivations behind those who develop or deploy algorithms. For example, a social network’s main algorithm might not show you posts that are necessarily life-enriching: All they care about is how to keep you on the website, so as to maximize the time and likelihood that you interact with their ads.
  4. Take control of your data and privacy. Algorithms feed on data. Training data is used to create an AI model in the first place, input data used to come up with predictions, and feedback data to refine the model. Some of your data might have already been used as training data, and it is used almost permanently as input data as we browse the web. Privacy regulations such as the GDPR help users gain more control over what data is being used for which purpose, but it’s better to pro-actively think about what data you share about yourself (every single ‘like’ of a statement, post or photo reveals preferences and affination with people, products, ideas and political views).
  5. Avoid dependency. By overly relying on the decision support provided by algorithms, we risk getting dependent on algorithms and organizations that deploy them. GPS navigation works well as long as the US government grants access to the satellites, you have sufficient battery charge on your mobile device, access to map data and clear line-of-sight to the sky. Miss any of these ingredients, and you are back to reading physical maps.

If the current trend is to continue, algorithms will continue to permeate our work and personal lives. Developing a fundamental understanding of their nature, application area and mechanics will help us use algorithms to our advantage while preserving our autonomy and independence.

About the authors

Simon Mueller Simon Mueller is a core member of the Strategy and Operations practice areas at Boston Consulting Group. He was formerly the general manager of the BCG Henderson Institute (BHI), which aims to surface, develop, and apply the next generation of corporate strategy ideas.

Simon advises technology clients on challenges such as business development, marketing, sales, product development, lean manufacturing, procurement strategy, cost reduction, operational efficiency, and corporate development.

At Harvard, where Simon received a Master in Public Administration, he focused on data analytics, technology policy, and performance management. He is the cofounder of the Harvard Future Society, which advises policy makers on the implications of converging technologies, such as artificial intelligence safety and privacy.

Julia DharJulia Dhar joined The Boston Consulting Group in 2009. She is the cofounder and leader of BeSmart, BCG's behavioral economics and insights initiative. In this role, she brings her passion and experience designing complex system transformation through nuanced behavioral change to clients in the public and private sectors.

Julia has advised and implemented transformational strategy initiatives across a range of social impact and public sector organizations, including economic development and planning, finance, labor, education, and social welfare. She works with private sector clients to integrate choice architecture and customer insights to improve the productivity, performance, and customer experience of organizations in sectors including airlines and travel and tourism, energy, IT, and telecommunications.

Before joining the firm, Julia worked as private secretary to the deputy prime minister and minister of finance in New Zealand. She also led a major study to increase private capital for public services as a member of the UK cabinet office's social investment and finance team.

The Decision Maker’s Playbook by Simon Mueller and Julia Dhar is out now, by FT Publishing, priced $21.99 (US) or £16.99 (UK). For more information go to: www.decisionmakersplaybook.com


binary code, data scientist featured

Women in tech - the why, what and how of building a career in data science

binary code, data scientist

By Joanna Hu, Principal Data Scientist, Exabeam

With a growing number of organisations recognising the financial, social and cultural benefits of recruiting more women into data science, isn’t it time to explore the opportunities on offer?

Like many women who graduate with a tech degree, it took me a couple of years to figure out that data science was my niche. Thankfully, I eventually found my way and went on to forge a rewarding career in this exciting field.

With advancements like machine learning and big data now in the frame, I’ve been lucky enough to contribute to discoveries and solve real-world problems in healthcare, energy, and now – as principal data scientist at Exabeam – the cybersecurity industry.

I’m not alone in thinking that data science is a rewarding field to work in. Based on overall job satisfaction scores, the role of data scientist is ranked #7 in the Glassdoor ’25 best jobs in the UK for 2019’ listing – with an average base salary of £46K.

A long heritage

Historically, women have made a significant contribution to the evolution of computer science.  Before the invention of electronic computers, women were more prominent in the computer science field, and contributed a lot to the invention of the first electronic computers.  As well as Joan Clarke, who worked alongside Alan Turing to crack the Enigma cyphers during WW2, the other female codebreakers at Bletchley included Margaret Rock, Mavis Lever and Ruth Briggs.

More recently, there’s been trailblazers like Dame Steve Shirley, who first embarked on a technical career at the prestigious Post Office Research Station in Dollis Hill, where the Colossus codebreaking computers used at Bletchley were created. Founding her own software company in 1962, her team of female freelancers would go on to undertake many cutting-edge projects – including programming the black box flight computer used in Concorde.

Today, a new generation of women are forging their futures within the tech sector. Coming from a diversity of backgrounds, they’re making great strides in the field of data science – and many have done so without an initial background in science, technology, engineering or mathematics (STEM).

A field rich with opportunities

Make no mistake, data scientists are in high demand. A recent study found that 80 per cent of UK businesses are looking to hire a data scientist in 2019, and IBM estimates that by 2020 the demand for data scientists and analysts will leap by 28 per cent.

That said, while women represent 47 per cent of the UK workforce, they only hold around 19 percent of all available tech jobs. Clearly, it’s time to redress the balance.

That’s certainly the opinion of bodies like the Alan Turing Institute and organisations like the International Women’s Day (IWD) movement. Indeed, the IWD #BalanceforBetter 2019 campaign is making great strides in changing hearts and minds – by showcasing how women in tech are achieving impressive outcomes for themselves and others.

The good news is a growing number of companies now acknowledge there are significant gains to be won by addressing the issue of gender inequality in their tech workforces. As a result, they’re eager to hire more female data scientists. Indeed, Gartner projects that in the next three years, both women and men will equally populate the role of chief data officer (CDO).

Why companies want more women in data jobs

Research organisations like McKinsey have found that highly diverse companies are 15 percent more likely to outperform those that are not gender diverse. Alongside enhanced financial performance, reports by analysts such as Morgan Stanley, McKinsey and Gartner confirm that having more women in the tech workforce creates a more cooperative and collaborative atmosphere.

Their research findings also highlight how women are more aware of risk, which in the field of big data is a major plus. What’s more, women tend to excel at communication, team nurturing and problem-solving—all vital qualities when working in the field of data, where outcomes depend on asking the right questions, and listening to the answers.

Finally, and perhaps most interestingly, the research findings illustrate how women are strong advocates for data-driven decisions and tend to be more solution-oriented than male counterparts.

I’m not a rocket scientist – can I make it in data science?

Absolutely. If you’re a curious person, are passionate about innovation, and have an interest in technology, then this may well be the career for you. Stephanie Glen’s recent blog – charting her life-changing journey from office cleaner to data scientist – highlights that as far as she’s concerned, a love of logic problems is the most important pre-requisite for the job.

Typically, the skill sets required include math, statistics, coding and system design. But, as a recent article in CIO magazine highlights, exacting true business value from data requires a unique combination of skills that includes storytelling and intuition.

Truth is, women with a passion for learning who want to try something new will find there’s a number of big-name tech companies out there that only too ready to help you develop the digital skills you need to embark on a career in data science. Plus, there are organisations like Girl Geeks that are proactively supporting women to enter and progress in the field.

Top tips?

If you’re already working in the tech field, or are ‘data science’ curious, then teach yourself the data science knowledge and network as much as you can.  Before deciding this was the path I wanted to commit to, I spent time talking to people about their work, went on workshops, joined weekend meetups and tried out small projects from the online courses.

These days, there are lots of resources available to women who want to make a go at it in this field. Find out about which new tools you’ll need to learn, then use your free time to hone your skills – pretty soon, you’ll become an expert.

When it comes to seeking out new job opportunities, follow good companies and people rather than high salaries. Ideally, you’ll want to work for companies that have intelligent leaders and care about their female talent. Most importantly, hunt down a great mentor and commit to continuously learning from superiors and peers.

Finally, believe in yourself and, no matter what roadblocks you face on the journey, don’t let anyone limit your potential.

Joanna HuAbout the author

Joanna has rich industrial working experience within data mining and big data analysis for healthcare institutions, energy companies, and retailers. Through her work she aims to help them identify frauds, predict risk and outcome, reduce cost, and estimate product qualities.

Joanna has a Ph.D. from University of California, Berkeley, in Nanotechnology and a Ph.D. from University of Michigan in computational earth sciences. Before joining Exabeam in 2015 as a senior data scientist she worked at Ayasdi as a data scientist building and improving algorithms for client healthcare institutions to produce the best treatments for patients. Since October 2018 Joanna has been principal data scientist at Exabeam.