At Interview Query, we love to hear from those who’ve successfully landed jobs in the data science field. To help the rest of our community, we’re sharing their career path stories and approach to interview preparation.
This week we caught up with Chandini Ramesh, who has held product analytics roles at Primer AI and Gloss Genius while attending graduate school at Georgetown University. We discussed their journey into product analytics, deciding between contract vs. full time work while being a graduate student, and ways to unlock the full potential of networking.
I graduated from college in 2018, where I studied industrial engineering. The first job I had out of college was at a semiconductor company, doing supply chain analytics. In the role, I ran reports, evaluated shipment efficiencies, and performed analysis around production planning to ensure it met the demand for specific products. After a year, I realized I wanted to be closer to strategy and work with a typical software/tech company.
That’s when I transitioned to my next role, which was at Bloom Global. Bloom is a supply chain software startup. My domain knowledge of supply chain analysis proved very easy to transfer. I found myself working as a sort of associate product manager, where I was involved with the entire product lifecycle, from writing requirements to design to feature development with the engineering team. It was a great role, but I really missed the analytical aspects my old analyst position.
Those two jobs gave me a huge amount of insight and wisdom, and pushed me to pivot fully into data analysis. I would have loved to stay with Bloom, but they just weren’t able to offer that opportunity as a smaller startup. I moved jobs again at that time, to Primer AI. There, I was able to work with product analytics, analyzing how customers use our product, and how we could optimize the customer journey.
I loved the role overall, I loved working with the product team, and by the end of two years I was convinced to apply for the graduate program that I am in currently. I wanted to dive deeper, and hoped by the program’s end that I would be able to bring more analytical expertise to the job I was currently doing. So that’s how I found my way into the Georgetown Master’s in Business Analytics, with an expected December 2023 graduation.
Unfortunately, I was laid off in October of last year from the company I had started grad school with. I was planning on switching firms anyway later in my degree, since it’s structured to support part-time working professionals, but that definitely accelerated my job hunt.
I started interviewing and applying to roles more geared towards what I wanted, which was a product analyst role. I was looking for a company where there was a bit more established data team, as they would have the scope for more complicated projects and more technical projects. I was able to network heavily during this time, mostly online, and I pretty quickly had a few different offers for contracts, internships, and a full time position. I was lucky to be able to choose between them.
Ultimately, I chose a contracting opportunity at Gloss Genius because I was still working on my Master’s. I viewed it as a way to gain relevant experience for six months, build my skills, and gain stories to tell of analytical projects during future interviews. It also gave me flexibility for applying to full time roles again in the fall when maybe the job market is a little bit better.
I really leaned on a community called Data Angels, for women in the data science world. We have a virtual coffee & donuts event through Slack that we run regularly, where you get matched with other professionals. At the start of my interview journey, I was regularly tuning in to the group in order to discuss the intersections of data science, engineering, product analytics, etc, and getting tidbits of advice throughout.
Besides the imparted wisdom on interviewing, it also gave me exposure to different companies. Members would discuss their experience at these organizations, while also posting jobs that they were currently hiring for, making it much easier to speak with a real person in the process.
I used LinkedIn, but when a listing came up I was interested in I would try to speak with someone from Data Angels. Occasionally, they would even be able to direct me to the hiring team to discuss the role directly. This was more useful for larger companies, but for startups I would often apply without an insider.
Product analytics definitely feels more niche as a field than other data science roles, and so the combination of job experience and Master’s made me an attractive candidate. I had a lot of relevant stories to share during interviews, and I could be extremely focused on my applications.
Gloss Genius is a startup but still has a rigorous interview process for the product analyst role. I had four rounds for this contract position:
They provided me with a product that they were considering a new feature for. They were curious how I would approach an analysis of the feature success, and how I would construct an A/B test. They were really looking to see how I determined a thorough understanding of the scope of the problem.
This round focused on product metric questions. They quizzed me on how I would investigate a key number that appeared to be down for the quarter; how would I test that metric? Where else could you investigate for trends across the company arising from the metrics decline? They would then provide additional information, letting me know that the hypothetical investigation had turned nothing up, but that a problem was persisting. Where else would I look afterward? This continued on for some time as we worked through the problem.
This is just a typical behavioral interview, with nothing too out of the ordinary. Keep a few key stories in mind that you’ve prepared beforehand that really highlight your strengths, and don’t be afraid to take a few moments to think before launching into an example.
The technical round involved not only SQL interview questions but also scenario-based data modeling. I was required to come up with the table design and format based on the information given, and then use those tables to answer queries with SQL. This is unique in my experience, as most product analyst interviews do not ask for the modeling piece.
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