A Career 360 During Maternity Leave | A Mother’s Day Interview with Kaggler Parul Pandey
Head of Data Analytics at Kaggle, Wendy Kan: This week, I had the pleasure of interviewing Parul Pandey, a Kaggle Notebooks Master, Data Science Evangelist at H2O.ai, and mother to a 5-year-old son. Parul shared the story of how she pivoted her career during maternity leave 5 years ago, and her experience in organizing Women in Data Science and Machine Learning groups.
As a fellow mother and data scientist, I found her story inspiring and wanted to spread the love and inspiration with the broader Kaggle community this Mother’s Day.
Wendy: What can you tell us about your academic and professional background? Did you code in school or at your previous job?
Parul: Academically, I’m an electrical engineer. I did quite a bit of coding as a part of my curriculum but also enjoyed it as a hobby during my undergraduate years. Professionally, I worked in the power distribution industry as a technical analyst before getting immersed in Data Science. My job entailed less coding and more of using tools, but I would still dabble in little programming activities as a side project during my free time.
What motivated you to learn machine learning? How did you pick up data science and machine learning? Did you start with the courses?
Since I was already into data analytics, machine learning was a natural choice for me. However, what really pushed me into the game was the movie Moneyball. I was fascinated by the analytics and data-based approaches that were used to build an entire baseball team. A few years ago, in 2012, severe power blackouts affected most of northern and eastern India — nearly 400 million people! Since my department was responsible for the analysis and planning of the power distribution network in Indian cities, I wondered if the same analytical principles could be applied to avoid similar incidents. The quest for the answers began, and that is how it all got started.
At my previous job, I crunched numbers, analyzed them to get insights, and performed predictive analysis. However, all these analyses were done using proprietary tools. I would sometimes wonder if the processes could be replicated using open source tools and the current best practices in data analysis, predictive analysis, etc. Sadly, due to a hectic schedule, I couldn’t give much time to these thoughts, but when I did get some time off during my maternity leave, I started looking for answers.
Like most people, I did a lot of MOOCs on platforms like Coursera and EdX. However, there were two things that I followed diligently. I made sure to complete a course before jumping on to another, and secondly, I tried to connect the things I learned in these courses to my official work. Sometimes it worked, and sometimes, it didn’t, but in the course, I learned a lot.
You’ve mentioned that maternity leave was a significant milestone in your professional career. Can you tell us more about this journey?
I actually reinvented my whole career during my maternity leave! I had a decent job but felt that my career was stagnating. Before maternity leave, I hardly had time to ponder over, but the break gave me a chance to reflect on my life and career, and if I was actually enjoying what I was doing.
At that time, I wasn’t thinking about particularly switching careers, but I just wanted to do something that I always liked — programming. I started with programming and eventually ended up doing a course on Machine learning. This was the tipping point, and I felt I naturally enjoyed this stuff. I thought that once I went back to the office, I would utilize the newly acquired knowledge to solve some issues that I was facing at work. Little did I know that it would be the start of a new phase of my life, both personally and professionally.
How did you learn about Kaggle?
Kaggle gets its fair share of mention in every MOOC, and I also got a first hang of it through one of the online courses that I was doing at that time. An algorithm implementation was being shown, and the instructor pointed to a website called Kaggle to download the dataset. I hopped on to the website and created a profile. I often visited the site to look for datasets and would end up scrolling through the notebooks. However, it took me some time to actually start participating.
Initially, I had the misconception that Kaggle was only a data science competition platform. When I look back now, I realize that I was so wrong about that. If there’s one thing I learned — it is that there is no better platform to learn the nuances of machine learning and data science than Kaggle.
That’s good to hear!
How did you manage your time learning new technical skills while being a new mom at the same time? How do you stay motivated in your journey to keep learning?
Being a first-time-mom is both challenging and overwhelming primarily because you have no idea what you are doing. ;) There is suddenly so much going on in your life that you start losing track of things.
The first few months were definitely hard, but then slowly, things started to improve and get easier all around. I created a schedule around my baby’s nap times. Contrary to what you would expect, my kid was a very light sleeper and took very short naps. There were times when I was fully immersed in an assignment, and suddenly there would be a cry which could scare the neighbors away! That was my cue to take a break. Then I would wait for him to fall asleep again, then pick up where I left off. This might sound frustrating, but because I enjoyed what I was learning so much, it almost didn’t matter how many breaks I had to take to get back into it.
Taking care of a child is a full-time job, and since we didn’t have any help at home, we had to manage everything ourselves. Keeping motivated in such times is essential since you tend to lose focus quickly. I created small goals for myself every day, and achieving them gave me a sense of accomplishment.
Did your husband or family play a significant role in your career switch?
Having a support system is vital when you decide to make a career switch. Having family or friends who believe in your decision is a significant confidence boost.
There were times when I was surrounded by self-doubt as to whether or not I was on the right track. It was during those times that my husband made me believe that I was making the right choice. He proofread my blogs, suggested new ideas to incorporate into them, and would provide the critical feedback I needed, while also taking care of our baby. My husband has been instrumental in shaping my career.
Curious, what inspired you to start writing a blog?
While I was doing the data science courses, I used to document everything in the form of notes. This helped me to better understand the topic at hand, and I could also revisit the concepts when needed. In 2018, I came to know about the Medium.com and how easy it was to publish an article here. So, I just started publishing my notes as blog posts on Medium. Of course, I didn’t get much traction at first, but putting it out into the world felt really good.
Eventually, I started sharing my posts to LinkedIn and began receiving kudos and valuable feedback from peers.
How did you know you were ready to transition from DS hobbyist to professional?
Data science is a continuously growing and evolving field, and as a result, you always have the feeling that you need to know more. I always felt that I needed to learn more before I began applying for jobs in Data Science, lest I was rejected.
One of the reasons for this feeling is how data science jobs are advertised. An applicant is required to know everything from statistics to NLP to computer vision with a sufficiently advanced level of experience in programming. I felt it would take me a decade to fulfill those requirements, and still, I wouldn’t be confident enough to call myself an expert! Hence, I didn’t apply for any jobs directly but instead tried to make a robust portfolio first. I worked on my Github profile, started writing blogs for publications like Towards Data Science, KDNuggets, and Datacamp and became active on Linkedin in the data science community. This helped me to get a voice and visibility at the same time.
Why did you start the Women in ML/DS community in Hyderabad?
During a meetup I conducted, I recognized that female participation was very low, and this continued in other meetups and conferences. I also observed that the female participants, if any, hardly asked any questions, instead they preferred asking questions personally than in the gathering. It was then I thought that why not have a separate meetup group for females interested in machine learning and data science?
This gave me a chance to understand what kept women from attending conferences and how we might address these issues. Fortunately, I came to know about the WiMLDS organization, and they didn’t have a local chapter in Hyderabad, India. I volunteered to create one, and the rest is history!
Do you believe having a women-specific community helps more women to join the field?
I definitely feel so. Female communities help to create a supportive space for other women. Women feel more comfortable speaking up, thereby motivating other women. However, even though such communities are thriving, it requires a collaborative effort from society to make diversity and inclusion a vital part of the ecosystem.
You did well (top 1%!) in the WiDS competition. Do you like these women-focused competitions?
The WiDS Datathon 2020 was a remarkable experience for me both in terms of learning and collaborating.
I teamed up with 3 of my colleagues at H2O.ai for this competition. A huge positive about this competition was that a lot more women were active in the discussion forum than an open-to-all competition. They shared research papers and blogs and even helped the fellow contestants with notebooks, which I find lacking in the other competitions. The chances of finding women to team up increases in such competitions as opposed to others. I wish more women would actively participate in all sorts of competitions. Still, for now, women-only formats make it easy to get more women involved.
Does being a mother change you in the way you work? Does it change the kind of job you look for?
I feel I’ve become better and more efficient in managing things now. Most importantly, I can manage with very less sleep too! I’ve started valuing and better prioritizing my time more since it’s so limited now.
Yes, job preferences have changed too! I prefer working remotely now. This way, I can manage my time and take good care of my kid without sacrificing any front.
I’m lucky that my current job at H2O.ai is a full distributed, remote team. I do most of my work when my kid is asleep or at school. This way, I don’t have to compromise on work and get to spend quality time with my child.
Did you ever fear that you might have to choose between having children and having a career?
Becoming a mother is a personal choice, and when a female decides to become a mother, she shouldn’t be made to choose between a career or a child. Unfortunately, this does happen all too often. I’ve seen women are denied promotions or projects because they would be going on maternity leave. Exceptions do exist, but this is still a fairly common phenomenon, and this makes me so sad. When I decided to become a mom, my focus was on having a healthy baby rather than a healthy career.
This Mother’s Day, do you have anything to say to other mothers and mothers-to-be?
Motherhood is a transition, and it’s common to feel angry, depressed, confused, and so many other emotions. Your life will change, but it’ll change for the better. Having a baby is having all of life’s most bittersweet moments come at you one after the other. Cherish and enjoy the moments with your kids, for they grow up very fast.
Indeed they do.
Thank you so much for your time, and for sharing your inspiring story with all of us. And of course, happy Mother’s Day!
Did you enjoy this interview? Let us know by adding your ‘Claps’ to the article. Read our 2019 Mother’s Day interview with Nicole Finnie