Inspired by our recent women in tech blog which highlighted three women in tech roles at Dataiku with STEM backgrounds, we wanted to continue onward with the same spirit, celebrating the wonderful women of Dataiku. However, this time, we mixed it up and talked to three ladies who have taken a less traditional path into the tech scene.
Meet Colleen Chen (solutions engineer, based in Australia), Triveni Gandhi (Responsible AI lead, based in the U.S.), and Stephanie Griffiths (AI evangelist, based in France)! In the interview and short video found below, they share unique perspectives and guidance for breaking into the tech space, navigating imposter syndrome, following your passions, and more.
Please introduce yourself and explain your background / what you were doing before you got into tech.
Colleen: I started my career with a background in urban planning and law, first working as a government lawyer, and then as a policy professional at the Defence Artificial Intelligence Centre in the Australian Department of Defence.
Triveni: Prior to being in tech, my focus was primarily on social sciences. My academic background includes a Ph.D. in political science and a Master’s in international relations. During my grad school years, I became interested in statistics and eventually ended up using a bit of R. These explorations allowed me to get a foothold in analytics, and I ended up getting involved in data analytics with a nonprofit. From there, my interests grew, and I began taking training courses for data science which helped guide me to Dataiku today.
Stephanie: Prior to Dataiku, I was on both the agency and client side of digital transformation. I also worked on the creation of three different companies in prototyping, fintech, and education — one had an exit, one was fairly successful, and the other failed. From each of those unique experiences, I gained expertise in a variety of areas. I also have experience in public services. I was a board member for VisitBritain, attracting visitors to the British economy, and acted as an advisor for the French Trade Ministry in Germany.
How has your unique background helped you in your current role? Were there specific experiences or events that propelled you to your career position today?
Triveni: Well, I started at Dataiku as a data scientist, and here that is a very customer-facing role, so my experience working with students and presenting to non-technical audiences was very helpful for the communication skills I needed as a data scientist. Additionally, having a background in social sciences has allowed me to see things a little differently than I would if I did not have this background. I am keen on not assuming objectivity, and I take everything with a grain of salt. In a broader sense, soci-technical perspectives are a growing area of concern in tech right now, so my background has helped me a lot in understanding this shift in the space.
Stephanie: During school, I was not always good at math, so I had to be extremely creative in order to find my own path and adapt to my school environment which was very math-centric. Eventually, I became very interested in the internet. I never exactly planned to work in tech, but I had the opportunity to join a tech company in the U.S. within the sales and marketing department. When I returned to France, I joined a startup, helping companies develop their websites.
As I followed my creative interests, my transition into the tech space was more of a natural transition. At the end of the day, what I really was interested in was helping businesses transform their relationships with their clients. I had studied philosophy, political science, and marketing, so I was very passionate about finding new ways for citizens to influence businesses and create a dialogue versus traditional advertising. This passion has been very helpful and has encouraged me to ask many “why” questions in tech.
When I was working as Chief Marketing Officer for an organization, I realized my organization was using AI as a buzzword and not as a tool — so, not really utilizing AI at all. This sparked my interest to learn more about the actual capabilities of AI.
Colleen: While working in policy and procurement at the Department of Defence, I was exposed to a diverse range of leading technologists in industry and academic institutions. Daily interactions with them inspired me to become a technologist myself and helped me develop an awareness of the latest trends in building data science projects. It also helped me identify the types of skills I needed to acquire to become a proficient data scientist.
As someone working in tech with a non-traditional background, have you ever experienced imposter syndrome? Do you have any guidance for others who may experience this feeling as they pursue a career in the world of tech?
Stephanie: Yes and no. There is always going to be more you can learn about, but it is also important to know that it is good to have a unique perspective. Recognizing that beyond a ground level of tech understanding, background diversity allows for the emergence of valuable and unique questions. Remember that everyone has a place. Tech is truly useful if it serves a purpose, answers a “why,” builds sustainable growth, and protects diversity. So, a 360-degree perspective on tech is the only way to go, and it can’t be achieved if you don’t collaborate with different talents (for example, designers, legal teams, philosophers, as well as data engineers, and data scientists). If you are not good at mathematics, that does not mean you can’t work in tech!
Colleen: The beauty of the data science community is that everyone is constantly learning due to the fast-moving nature of the industry as well as the breadth and depth of the field. Some of my most knowledgeable colleagues and clients are also the most modest, supportive, and patient. Therefore, while I feel nervous about certain topics from time to time, I am constantly reminding myself that it is okay to be learning as long as I am putting forth my best efforts to learn quickly.
My background in law and design has prepared me well for constantly learning complex rules and systems, so, from a workload perspective, the need to stay on top of new technical topics did not faze me. I actually really enjoy the challenge — especially since Dataiku has such a robust learning culture in which we are given many opportunities to learn together.
Triveni: Yes, of course. I think even those with a tech background will experience these feelings sometimes. My advice is to learn how to showcase what you can do in addition to your technical skills — i.e., What do you bring to the table on top of the tech stuff that will add value? What can you do that other people cannot? Reminding myself of the unique skills that I bring to the table is how I work to counter imposter syndrome when it pops up.
Tech is often perceived as a male-dominated field. Are your experiences congruent to this common assumption? How have other women in the field impacted or supported your career along the way?
Colleen: Yes, tech is a male-dominated field, and we are lucky at Dataiku to have a well-balanced team of technologists who are able to be role models for others. In my case, I am grateful for the mentorship from senior solutions engineer Vicent Osabel and lead data scientist May Phang. I know they are only one Slack message away to help answer any questions I have. Not only that, a question often brings about a quick chat in which they teach me how to think through the issue and share what it was like when they were learning about these topics.
Outside of Dataiku, I have a few mentors who practice the art of tough love extremely well. It takes a village!
Stephanie: My best mentors have been my grandmother and my mum! My grandmother had a pharmacy and told me she never had the feeling of “working” because she was passionate about what she was doing. My mum always encouraged me to work hard, always believed in me, and helped me a lot when my kids were small.
To answer the first question, tech is slowly changing, and I feel Dataiku is a good example of diversity. I have lots of (tech) questions and feel totally at ease asking for support from anyone.
Triveni: I would say yes. This has been evolving, but there is still a long way to go.
I am lucky to have had the support of women at Dataiku — especially when I started and there were fewer women on the tech side of the house. Mentorship and community through ERGs were so important for me and many others. We used our collective voice to highlight the gender imbalance across technical teams, and in doing so activated a number of male allies across leadership, in turn leading to more inclusive hiring practices. Now, as we grow the company, I am conscious of the support I received early on, and am doing my best to pay it forward.
What general advice do you have for women, specifically from non-stem backgrounds, as they begin or transition into new career opportunities?
Triveni: The main thing I notice is that most people can pick up tech skills, so being able to showcase your unique background is crucial. Your subject matter expertise is very valuable, so use that to your advantage. Build out some cool projects that truly demonstrate your knowledge of particular domains.
Colleen: My advice would be to take the plunge, be prepared for hard work, and find a pathway that suits you. When I look back at my journey, the toughest part was knowing where to start because there was so much to learn. I initially enrolled at university and subscribed to a few online courses, but the progress was too slow for my liking so, instead, I found a junior technical role in a data science company that allowed me to build my skills on the job and learn every day through necessity.
My brilliant supervisor Grant Case saw my potential and invested in training me for the position. This has been the most effective way of learning for me. As with any other discipline, doing my job day-in-day-out has taught me how to learn and has helped me see through the unnecessary jargon and gatekeeping that can make one feel that they do not belong to the tech industry.
Stephanie: Follow your gut and don’t be afraid to try new things. Just start! We need people who question things and bring new perspectives. There are many areas where we need skills you may not think of as traditional tech skills such as AI ethics or linguistics in localization. Data science is a highly collaborative field where we need all different kinds of knowledge. Don’t believe that you don’t belong simply because you do not yet have tech experience.
Perhaps Colleen, Triveni, and Stephanie’s journey of embracing unique talents has resonated with you. From our EmpoWer ERG to our scholarship fund, Dataiku is dedicated to helping women feel confident carving their career paths in tech no matter what background they come from. Check out this article featuring women in sales leadership roles at Dataiku for more inspiration.