OTT platforms like Amazon Prime and Netflix have changed the way we consume entertainment, through a rich and diverse layer of personalized content driven by powerful algorithms.
Saurabh Puri, our next pathbreaker, Business Intelligence Engineering Manager for Prime Video Channels, Payments and Subscriptions at Amazon (Seattle), leads a global team spread across US, UK and India, and is responsible for driving the design, development and maintenance of innovative and scalable analytics solutions for the Prime Video Channels business.
Saurabh talks to Shyam Krishnamurthy from The Interview Portal about his exposure to business and data analysis as a young teenager while helping his father track business inventory and sales, which shaped his interest in data science.
For students, the key differentiator for any business lies in quantitative analysis and the ability to address large scale data analytics challenges that aid in decision making!
Saurabh, Your background?
I was born and raised in Kolkata, West Bengal, India. My mother is a house maker and my father is a small business owner as a cosmetic retailer. My parents always valued education and wanted me to have the best education. I hold a Master of Science degree in Business Analytics and Project Management from the University of Connecticut School of Business, and a Bachelor of Engineering degree in Computer Science from the Manipal Institute of Technology (India). I currently work at Amazon, heading the analytics in the US for Prime Video Channels. Outside of work I enjoy the outdoors and hiking, reading biographies, watching informational videos on YouTube, and hanging out with my wife and my dog.
As a young teenager, I regularly helped my father in his shop with accounting, routinely checking the inventory over the weekends and summer vacations. Every summer break, I would complete my vacation homework in the first week and help my father in his business. Early in my teenage years, I realized my knack for mathematics and business data analysis. My father would regularly try to forecast the sales in his shop during peak periods such as Diwali and wedding season, but he did not have a structured way to do so. One summer (it was either my 7th or 8th standard), I completed my mathematics homework that covered basic statistics like overview of mean, median and mode with examples related to shopping spends. After learning the basics, I looked through my father’s account of item sales for the previous year and applied learnings from my homework to help him calculate the mean of popular items sold monthly and during peak periods. This helped him secure the right inventory and rightly approximate the quantity to stock by item category. I did this yearly for a couple of years, and over time I realized that with the help of a computer I can automate these calculations using MS Excel. Learning from this experience, I planned to obtain a Bachelor’s degree in Computer Science. I then completed a Bachelor of Engineering in Computer Science from Manipal Institute of Technology (MIT) in India. After working for Accenture for a few years, I continued to pursue my passion for business and data analysis by enrolling into a Master of Science degree in Business Analytics and Project Management at University of Connecticut in the United States.
What did you do for graduation/post-graduation?
I graduated with a Bachelor of Engineering in Computer Science from the Manipal Institute of Technology in Karnataka, India in 2011. Following my teenage passion for data analytics, I pursued my Masters in Business Analytics and Project Management from the University of Connecticut in the United States and graduated with an MS degree in 2016.
What made you choose such an offbeat, unconventional and cool career?
My interest in business and data analysis started as a young teenager helping my father track inventory and sales for his small business in Kolkata. I did basic data analysis for sales, by sorting “most sold” products by quantity, category, and revenue. I also tried to predict the sales during Diwali months by using simple mean of sales for the last year-two years. When I was in the 11th standard, my father purchased a personal computer for our home. That unlocked a wealth of resources for me. I learned about rolling averages method and using MS Excel. I loved the computer and the resources the computer and google search offered. This experience shaped my interest in pursuing a Bachelor’s degree in Computer Science, and business analysis thereafter.
After graduating, I worked with Accenture in India and the Netherlands for a few years. At Accenture, I worked with a giant credit card company and European Investment Management company who were the clients.
My work at Accenture covered descriptive analytics, analyzing historic trends, and creating business reports to help our businesses grow. In my position at that time, I didn’t have the influence and position to make recommendations and business decisions for clients, but I was exposed to predictive analytics and how I could leverage it in drawing insights to make recommendations to a client-side colleague. This partnership sparked my curiosity in statistics and data analytics and eventually paved the path for me pursuing a Master’s Degree in Business Analytics and Project management. The work of Andrew NG, a globally recognized leader in machine learning influenced me, and encouraged my uncle, Tarun A, who has consistently applied data analysis to his avid hobby of stock trading. Inspired by these events, people and the potential of data analytics and its widespread application at corporations, I moved to the United States in January 2015 to pursue a Master of Science degree in Business Analytics and Project Management at the University of Connecticut School of business.
How did you plan the steps to get into the career you wanted? Or how did you make a transition to a new career? Tell us about your career path
Graduating with a degree in Computer Science and then a Master’s Degree in Business Analytics and Project Management helped me land an internship at a startup called Inturn in New York. Inturn helped companies liquidate excess inventory. My role in the company as an intern (pun not intended) was to think through appropriate KPIs; design, develop and maintain interactive dashboards. This is where I applied my learning from the Master’s Program and prior work experience at Accenture.
During my bachelors at MIT, I was introduced to finance and was intrigued by the workings of investment management companies. Since then, I wanted to work with an Investment Bank. Once I graduated from UConn with a Master’s degree, I was offered a job at TD Asset Management in New York City. There, I worked on creating and enhancing the proprietary Analytics platform of the Asset Management Portfolio that generated multiple business metrics and analysis for traders. I also worked on stress and scenario testing of portfolios by simulating the impact of different market scenarios on a portfolio in order to identify potential risks and vulnerabilities.
After working with TD for 1.5 years, I started to interview with my dream product/tech companies, and to my delight I was offered a position at Amazon within the Prime Video division in 2018. I have been at Amazon since then. At Amazon, I previously led the Prime Video sports analytics team driving large-scale analytics for Thursday Night Football on Prime Video, and set up near real-time analytics solutions for sports streaming events. I also laid the foundational analytics solutions for big-ticket third-party subscription launches on Prime Video such as NBA, MLB and PGA. I’ve held various roles within Amazon and Prime Video, progressively taking up bigger and better problems to solve, and growing in level and responsibility.
How did you get your first break?
My first job with Accenture was through Campus placements at Manipal Institute of Technology. However, I started working as a Java Developer at Accenture. Quickly, I worked with my managers and leaders to shift my career onto data and business – something that I was passionate about pursuing.
My first break in US came through when I was hired as an Analytics Engineering Intern at a start-up called Inturn in New York. The career services office at the University of Connecticut helped polish my resume to industry standards and provided insights into approaching my internship/job search. I continued to apply for internships relevant to my experience and passion and finally got an opportunity to join Inturn in Jan 2016 and continued through May 2016. While interning, I continued to develop my data visualization and predictive analytics skills; and applied for full time opportunities months before my planned graduation. My internship combined with Accenture experience helped me get phone screen with multiple companies and I eventually landed a full-time opportunity with TD.
What were some of the challenges you faced? How did you address them?
One of the biggest challenges I’ve faced was to get initial phone screens for internships and full-time jobs. I continued to experiment with my resume and reaching out to recruiters/employees from an organization to refer me though their referral links. Over time, I realize that it is critical to have a well stitched resume and network as much as possible to slightly increase chances of getting the first phone call.
Where do you work now? Tell us about your current role
I currently work as a Business Intelligence Engineering Manager for Prime Video Channels, Payments and Subscriptions leading a global team spread across US, UK and India. My team includes Business Intelligence, Software and Data Engineers across US, UK and India. I am responsible for driving the design, development and maintenance of innovative and scalable analytics solutions for the Prime Video Channels business.
My team captures and engineers the transaction, payments and subscription data and is responsible for all the processing of the data to make it usable. Additionally, we analyze the performance of our subscription business across multiple channels we offer; such as what’s driving the business and what can be done better for our customers.
What problems do you solve?
I work with multiple stakeholders on problems related to subscription, payments and streaming to drive data analytics that are timely, accurate and actionable. The biggest challenge is prioritization and finding the best problem to solve first. I continue to get multiple problem statements with varying levels of impact and the team gets entangled in the details and complexities. It’s important to juggle between the business impact and technical uplift required to achieve the impact. To address this, I usually work with an impact vs effort matrix to determine the next problem to solve.
What skills are needed for your role? How did you acquire the skills?
Key skills required are strong data analytics skills, technical and cross-functional leadership, strong written and oral communication, business acumen, process improvement, project management and people management. I’ve gained these skills over the years working in the consulting, investment management and tech domains.
What’s a typical day like?
A typical day involves speaking with stakeholders on narrowing the next problem to solve, questions to answer, and working with my team to unblock any bottlenecks. I love getting to the core of a problem and usually analyze billions of rows of data and set up automated analytical dashboards. I regularly review the work of my team and other teams within Amazon. I spend a significant time working cross-functionally in building our long-term vision for analytics within Prime Video. I regularly mentor analytics professionals within and outside Amazon.
What is it you love about this job?
As pointed above, I am very passionate about data and love what I do. I love the depth and breadth of problems I solve, and love to create positive experiences for millions of customers streaming content on Prime Video.
How does your work benefit society?
My work benefits millions of Prime Video streamers worldwide. I help recommend changes to the Prime Video platform so our customers can find the content they enjoy faster ☺
Tell us an example of a specific memorable work you did that is very close to you!
My most memorable experience was when prime Video streamed the Thursday Night exclusive game in 2020 for the first time. The experience was magical and I had to solve one of the biggest engineering challenges by setting up a near real-time petabyte scale reporting and analytics. Senior leadership at Prime Video and Amazon at large appreciated my work.
Your advice to students based on your experience?
Start with the problem that you’re most passionate about. If you want to build a career in analytics, learn the basics of SQL, python and get a dataset on a topic that you’re interested in and find insights. Take up small projects to learn and explore, and continue on to take on larger goals/projects in the field.
I want to continue solving large-scale analytics problems for businesses and stay up-to-date with emerging trends in analytics. Someday, I want to create a course and teach my learnings to an eager and aspiring audience.