After completing his undergraduate in Engineering, Ravi Vijayaraghavan went on to do his PhD. His PhD thesis was, in the then (1990s) emerging area of computational modelling and optimization. This is where Ravi first developed skills in Numerical/Mathematical Modelling, Statistics, Optimization, Non-linear Systems and emerging Machine Learning techniques such as neural networks. He then joined Ford Scientific Research Labs where he applied this expertise to various problems in Engineering, Materials Science and Physics. Later Ravi got interested in Business Analytics. He moved over to a new role to set up a cross-functional analytics team. This was his first role where he was applying his data science and computation background to solve business problems in marketing, sales, strategy etc. rather than in the pure science and engineering domain.
What interested you in learning Data Analytics?
Ravi Vijayaraghavan: Even while working on my undergraduate project in my final year, I had developed a passion for computer simulation and modeling. This passion for mathematically modeling real-world systems on the computer and making predictions using data only grew over the next 3 decades and while the names, jargons, domains etc. evolved over the years, this has remained the common theme of my career.
What was the first dataset you remember working with? What did you do with it?
Ravi Vijayaraghavan: I will talk about the first business dataset I worked with. We were building a vehicle volume allocation model that would be based on historical data on vehicle sales, historical auto dealership performance, manufacturing capacity, historical currency exchange rates and various demand and pricing data/attributes provide the right allocation of vehicles to various international markets.
Was there a specific “aha” moment when you realized the power of data?
Ravi Vijayaraghavan: The key “aha” moment for any analytics or data science leader is when data-driven models translate into enhanced decision-making ability for humans or machines and as a result we are able to generate a meaningful “lift” in a real outcome. That is when the rubber really meets the road. Fortunately, at Flipkart there is no shortage of such opportunities since our decision-making process is fundamentally data-driven.
What is your typical day-in-a-life in your current job? Where do you spend most of your time?
Ravi Vijayaraghavan: Given that Flipkart is a technology/internet company, data is absolutely core to both human and systemic decision-making at Flipkart. This makes the life of an analytics professional at Flipkart both exciting and busy. In my current role, I spend time in problem-solving, technically mentoring the team, keeping up with the state-of-the-art in the field and working with stakeholders including business, product and technology teams.
How do you stay updated on the latest trends in Data Analytics? Which are the Data Analytics resources (i.e. blogs/websites/apps) you visit regularly?
Ravi Vijayaraghavan: I spend time on reading technical books/literature and continuing to learn from online resources.
Share the names of 3 people that you follow in the field of Data Science.
Ravi Vijayaraghavan: Andrew Ng, Peter Norvig, Hal Varian and many others….
Team, Skills and Tools
Which are your favourite Data Analytics Tools that you use to perform in your job, and what are the other tools used widely in your team?
Ravi Vijayaraghavan: R, Python, Tensorflow
What are the different roles and skills within your data team?
Ravi Vijayaraghavan: It is a mix of Business analytics people who specialize in business problem solving with analytic, data and science and decision scientists who possess deeper statistical modeling and machine learning skills. We also collaborate/partner closely with the Data Platform team that has deep data engineering skills.
Help describe some examples of the kind of problems your team is solving in this year?
Ravi Vijayaraghavan: Nowadays we are working on customer growth and loyalty, customer experience, pricing and selection/assortment. These are some of the key problems of online retail that are best solved by data analytics and science.
How do you measure the performance of your team?
Ravi Vijayaraghavan: It is a mix of technical competency/depth, business impact and contribution to organization development.
Advice to Aspiring Data Scientists
According to you, what are the top skills, both technical and soft-skills that are needed for Data Analysts and Data Scientists?
Ravi Vijayaraghavan: A good understanding of the business domain and priorities, ability to work with business and product stakeholders, ability to solve problems, a deep intuition for data and patterns in data, training in analytics and data science and ability to be hands-on.
What is your advice for newbies, Data Science students or practitioners who are looking at building a career in Data Analytics industry?
- Develop an intuition for data and patterns in data
- Develop a passion for problem-solving and a deep understanding of business or problem domain
- Develop skills in data processing/manipulation and programming languages such as R and Python
- Read and keep yourself current – data analytics and data science are fast moving fields
What are the changing trends that you foresee in the field of Data Science and what do you recommend the current crop of data analysts do to keep pace?
Ravi Vijayaraghavan: Over the last decade or so, there has been a lot progress in data engineering. This has made it feasible to instrument, process and build models on really large unstructured data sets (Text, speech, image etc.). The other major trend, piggybacking on this (i.e computation power and availability of large data sets), in the last 5 years or so is the emergence of deep learning (re-emergence of Neural Networks).
Would you like to share few words about the work we are doing at Digital Vidya in developing Data Analytics Talent for the industry?
Creating a talent pool in India with Practical hands-on experience in Analytics and Data Science is the need of the hour. Companies are looking to invest heavily in making their business technology and data driven, but have a hard time finding deep high quality talent in this area. Platforms like Digital Vidya are critical to filling this gap.
To know more about Ravi Vijayaraghavan, you can check out his LinkedIn.
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