Lindsey ZuloagaDr. Lindsey Zuloaga is the Chief Data Scientist at HireVue, managing a team that builds and validates machine learning algorithms to predict job-related outcomes.

As an academic researcher with a Ph.D. in Applied Physics, she has performed novel experiments and data analysis, resulting in scientific publications with applications in medicine, sensing, and signal processing. Lindsey started her data science career in the healthcare space, striving to improve the lives of people with chronic health conditions. At HireVue, she is working to completely transform traditional interviewing with a platform that focuses on understanding more of the candidate as a whole person, including interview responses, coding abilities, and cognitive skills as opposed to just the facts shown on a CV.

Tell us a bit about yourself, background and your current role

I started my career after several years of studying, initially earning my Bachelor of Science degree in Applied Physics from the University of Utah and then going on to gain a Ph.D. in Applied Physics from Rice University. In my first Data Science role, I used these skills in the healthcare space, specifically helping those with chronic illnesses.

In 2016, I joined HireVue as a Data Scientist. I was later promoted to Director of Data Science in 2017 and since 2020, I have acted as Chief Data Scientist. Since the Spring of 2021, I have overseen both the Data Science and Business Intelligence teams.

In my role, I work with my team to build and transform traditional interviewing processes using the power of Machine Learning (ML). HireVue’s platform and software enables hiring teams and recruiters to better understand candidates, using tools to analyse vocabulary, gameplay behaviour, and code quality to evaluate candidates for job opportunities. Our platform focuses on efficiency and consistency; we give applicants equal opportunities by offering job-relevant assessments while mitigating biases in gender, age, and ethnicity that are so often a problem in hiring.

Did you ever sit down and plan your career?

Not at all! It is contrary to what many people believe, but I think goal-setting can often be limiting. I have found that following what I’m interested in has led me to some great places. It has also allowed me to do things that I might not have had the confidence to plan for myself. As an example, I never would have thought it was possible to get a PhD in Physics when I was younger. No one in my family had gone to college. That just seemed like something that a certain kind of person did, and I wasn’t smart enough. But I loved Physics and I knew that I wanted to learn about it, so I figured the worst thing that could happen is that it would get too hard and I’d have to change majors. I kept moving along that path, got involved in research during my undergrad, and ended up applying to grad programs.

I got accepted to a PhD and continued working on things that I found interesting. When I finished my PhD I received the award for the most outstanding thesis that year. I was extremely honoured and realised that maybe I am the “kind of person” who achieves things like that after all. I don’t think it would have been productive for me to set a goal of doing that, it came from me following my interests and passions. As I moved through my career, I became more interested in data and applying for jobs made me feel strongly that our system of hiring is broken, which led me to my work at HireVue. Again, it may be a little unconventional, but this approach has allowed me to experience more and build a history that is unique to me.

Have you faced any career challenges along the way and how did you overcome these?

One of the most difficult experiences I’ve had was the transition from academia to industry. Coming out of my postdoctoral role, I was overqualified for many entry-level jobs, but at the same time, I’d never had an industry job before, so it is a strange position to be in. I mistakenly thought my resume would speak for itself and I greatly underestimated the value of connections.

I worked on learning the technical skills necessary to transition to Data Science, all while getting involved with the local community of Data Scientists and learning what companies were doing in the space. The job search can be a difficult time for people. Often there are hundreds (or thousands) of applicants for a single role, so the numbers are just not in your favour. It is kind of like dating, you have to try a lot of things before you find a match. It is important to push through that and try not to get discouraged. Rejection is a normal part of the process.

What has been your biggest career achievement to date?

In 2018 I received the Women Tech Council’s Innovator of the Year Award. Being seen as an innovator by the council was a huge honour and I think that solidified in my mind that innovation has been a theme in my work and that it is a north star for me.

What one thing do you believe has been a major factor in you achieving success?

As I mentioned, I follow my curiosity. What follows is work that I care about and I’m almost never bored. I think caring about what you do makes all the difference. Now that I am a leader, I see it so clearly in my employees. Work does not have to be your life – I have two small children, it can’t be! – but passion and interest are the top ingredients to a successful career in my view.

What top tips would you give to an individual who is trying to excel in their career in technology?

Take advantage of all the great content online to hone your technical skills (such as edX, Coursera, Udemy) and network. I know it sounds nauseating, but view it as sharing your interests with like-minded people. Local meetups are a great way to get connected to others in your area.

Do you believe there are still barriers for success for women working in tech, if so, how can these barriers be overcome?

I feel very lucky to live in a time where women are more welcome than ever in science and technology, but of course, change happens slowly. There are still a lot of factors at play as to why women are underrepresented in tech and particularly in tech leadership. I think the focus on STEAM for young girls is a crucial part of the solution, along with making sure women serve as role models.

What do you think companies can do to support to progress the careers of women working in technology?

Flexibility is huge. Despite all the progress of recent decades, women still bear the brunt of child work and housework, even those who work outside the home as much as their partners. I feel incredibly lucky to have had adequate maternity leave and the flexibility to work from home so that I can be around for many of the important moments in my children’s lives. I block out 30 minutes every afternoon to go pick up my son from school.

In the workplace, Covid has normalised the fact that we have families and personal responsibilities. Earlier this year, I had a female colleague reach out to thank me for telling everyone at a meeting that my camera was off because I was nursing my newborn. It was a small thing, but very powerful in making other women feel like they don’t have to hide the realities of what is happening at home.

There are currently only 21%of women working in tech, if you could wave a magic wand, what is the one thing you would do to accelerate the pace of change for women in the industry?

If I had a magic wand, I would just put more women in technical roles. I’ve noticed that when there is a critical mass of women on tech teams, the team dynamic changes in a way that makes it more inviting to other women. There is an association of technical roles with masculinity for a reason – there are a lot of men! With more women in the field, we can change that association.

What resources do you recommend for women working in tech?

Nothing specific, but I would say always keep a pulse on how your skills could be applicable to different areas or industries. Your career can take an interesting and unique path if you are open to applying your skills to work on what you care about, which may change over time.