Interview with Bogdan Nedanov — Data Science, Remote Work, Shopify, Working with Product Managers, and more [Product Mayday, EP.02]
All views, opinions and statements are my own.
Greetings, Romulo here! 👋
Welcome to the second post of my series of interviews with successful Product Managers (or peers of Product Managers, as you will see below), founders, and entrepreneurs out there. It’s a core element of the vision and MVP for Product Mayday, my most recent project focused on giving my time and experience back to the world. Read more here.
My guest today is Bogdan Nedanov, Retail Data Science Leader at Shopify, an all-in-one commerce platform to start, run, and grow a business that currently powers over 1,000,000 businesses worldwide.
Bogdan and I worked together in a previous life, right when he started his career in Data Science and developed the passion for the combination of data, technology, problem solving, and innovation. Given his successful trajectory and many stories to tell, I reached out to him and discussed the outline for this interview, which quickly evolved from “working with Product Managers” to broader themes on his passion for Data Science, thoughts on Remote Work, and his most recent experience with Shopify.
I want to thank Bogdan for his time and invite you to learn from this great conversation.
Enjoy!
Quick Bio
Let’s start with the basics. Tell us more about your career trajectory?
I have a PhD in Economics and my background is very quant and stats based.
Early on in my career, when I joined Capital One, I was fortunate to get exposure to machine learning techniques that I hadn’t previously seen in academia. There, I teamed up with great people and worked on things like predicting the amount of cash someone would have in their account and nudging customers to use a particular channel or mobile app feature, all very much oriented to the customer experience.
Fast forward a couple of years, I found myself leading teams working on client-facing machine learning projects focused on automation, first with Deloitte and later on with Wayfair. I could clearly see how the tech-driven automation via machine learning, computer vision, and natural language processing was connected with the business and the customer experience.
Right now, I lead the Retail Data Group at Shopify, focused on building out the POS (Point of Sales) product for Shopify Merchants interested in having an omni-channel customer-facing experience, selling both online and in-person.
Big topics these days: Data Science, Remote Work, and Shopify
Data Science: Explain this passion and what makes you "tick"
I’d say a lot of great data scientists have a desire to explain things. They are naturally curious and interested in understanding every detail. That’s something that drew me to the field. I love the ambiguity that is associated with data-related problems.
Every problem is unique and as you go from project to project, you never have the perfect data to solve your problem. To get around these data limitations, your solutions often need to be both technical and creative. Sometimes you need to be scrappy in your approach, while other times you need high statistical rigor to really understand the causal relationships in your data. When all of those pieces come together, work becomes challenging and rewarding at the same time.
Remote Work: Your journey to date and quick thoughts on how you see the future of work
Before the pandemic started, I had always been a big "in-the-office person," so pivoting to the remote world was a scary transition. Being in the office has always helped me form relationships and build trust with coworkers, and it became even more relevant as I moved from being an individual contributor to leading teams.
I joined Shopify after the pandemic had already begun and the remote work experience hasn’t been what I thought it would be. Productivity has been great and I’ve been able to build a lot of those relationships that I was hoping to have.
In my opinion, some of the bigger challenges on the technical side are related to onboarding new team members, particularly those who are relatively new to the industry, and creating the infrastructure to help them succeed. Luckily, Shopify has a number of tools and resources to support that.
For example, we frequently do pair programming, which helps folks start off and gain momentum, but it also gets individuals to work together and not feel alone when they are at home and there’s no one around. Thinking about the right team rituals is even more critical these days, as many of us have never met in person.
It’s worth noting that back in July, Shopify announced that we would go 100% remote. That has unlocked a number of new opportunities for us, like getting access to the best talent around the world. In the end, remote work is a trend that’s been going on for a while and COVID-19 has just accelerated it.
Shopify: It’s on fire these days! One of my favorite tech stories in the middle of such a challenging time — what's unique about the company and its culture?
I’m still relatively new at Shopify, but one thing I’ve definitely noticed is how everyone is super aligned on the mission: making commerce better for everyone.
It sounds a bit cliche, since every company has a mission “on the wall” and people talk about that all the time, but it’s pretty amazing to think how we impact people’s lives all over the world. Starting a business is incredibly difficult, there’s so much friction. Being able to automate a lot of that, simplify it, and let entrepreneurs do what they do best is quite empowering.
One thing that has really stuck with me is that I have many coworkers who are store owners and run their own businesses online (on the side). Putting it in perspective, running a business is not as simple as opening a social media account, and they can still do it because the product is that good. Hence, the great trajectory of the company so far.
Also, when starting a new project, we put a lot of thought into pairing the right individuals from different backgrounds, so that you always have a diverse combination of Engineers, Product Managers, UX, and Data influencing the direction of the product. It is an environment where speaking up is encouraged and you always feel heard — that creates a big sense of ownership over your roadmap and autonomy to make decisions.
If people want to learn more about what’s going on these days and the problems we're solving, they can visit our Data Science & Engineering blog (link here).
Working with Product Managers (PMs)
How does the day-to-day look like?
PMs are the glue that binds teams together. They have the vision, understand our merchants and their needs, drive each project forward, and get the various stakeholders aligned. It's a critical job and it helps us identify the right opportunities, build them out as efficiently as possible, and deliver across the finish line.
What are the things that PMs should start, stop, and continue doing to work well with Data Scientists?
I think that being more technically aware of what is or isn't possible based on the current tech stack and available data is extremely helpful for a PM. Sometimes you have an idea, but it’s just not possible with the data you have. By being more "tech savvy," PMs can better identify investments needed, set the right KPIs, communicate with senior leadership, and plan the various milestones ahead.
Also, it's important to stop solutioning the problem before getting the right teams involved — I’ve been guilty of that a few times in my career…who hasn’t, right? It’s not within the PM’s scope to approach other teams with a solution baked.
For example, a PM is planning an experiment and he/she needs access to a particular set of data. It’s very tempting to approach the Data team with a request to pull “this specific set of customers aggregated in a certain way,” but that’s the moment when we collectively miss a huge opportunity. Different functions approach problems from different perspectives. In this particular example, an early engagement with the Data team could have changed the requirements for proving out the hypothesis or even the approach altogether.
As companies grow, what are your thoughts on striking a good balance between delivering on the near-term priorities and continue driving toward a big, bold vision?
You have to go back to “first principles” and constantly assess the value of what you are doing right now and where that will put you — and your team, product, and company — in six months. Sometimes, people get really hung up on incremental changes and lose sight of many other opportunities around with great ROI (Return On Investment).
This is a great opportunity for PMs and Data teams to partner and make the right call in terms of what needs to be optimized and what new bold ideas are out there. This includes stopping work (shocking, huh?) and prioritizing tech debt clean-up, which if not tackled as a strategic lever, ends up holding teams back in the long run.
Lightning Round
What’s something that everyone should be learning right now?
SQL and Python. MOOCS (Massive Open Online Courses) are everywhere, so this is a great way to learn and differentiate yourself, regardless of your current role.
Data is driving every decision, so being scrappy and pulling your own data gives you an edge when you are competing for internal resources. You don’t want to be stuck and let this one big idea or opportunity pass just because you can’t find someone to run a few queries for an initial “gut check.”
What are you reading these days? Is there a book that you would like people to know about?
The first one is a novel, Contact by Carl Sagan (link here). I watched the movie as a kid. It was way ahead of its time. It has a female protagonist, who is a scientist and an engineer, and interestingly enough, she doesn’t get saved by anyone. The book is even better than the movie and it raises many interesting philosophical questions about life and the universe.
Another one is Proteinaholic by Garth Davis (link here). It’s on the topic of nutritional biochemistry, which is something I’m really passionate about. It looks at the effects of consuming amino acids and it has a really good literature review of multiple studies on this topic. For context, a lot of recent research has uncovered the negative effects of consuming too much protein.
What’s the one productivity trick that only you know about?
I find meditation to be extremely helpful. Every morning, I meditate for about 10 minutes, either with one of two apps: Waking Up with Sam Harris (link here) or Headspace (link here). They’re both great and meditation helps me with stress management through the day.
Another one that is not exactly secret knowledge is leaving the phone in the other room while working at home — simple, but really effective in terms of increasing my productivity.
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That’s a wrap!
Since I have you here, please consider reading my previous posts:
- From this same series, I interviewed Nick Norcross, Director of Product at Tala, a financial technology company on a mission to build a financial system that works for everyone (link here).
- I have also kicked off a new series named Year of Books 2021. My latest post has my takeaways on the book “No Rules Rules: Netflix and the Culture of Reinvention by Reed Hastings and Erin Meyer” (link here).
Thank you again for your support and looking forward to continuing my journey with you on Medium.
Cheers, Romulo
