I am a data scientist by profession and the buzz question I get asked always is ‘what is the objective of my job?’ I quote Carly Fiorina (former CEO of HP) in my answer “The goal is to turn data into information and information into insight.” And I believe it’s these insights that lead to effective decision making.
My tryst with analytics dates back to my college days in IIT Kanpur. I got the chance to explore data science and operations research as a part of the curriculum and slowly started solving forecasting problems with only 10 data points. This got me thinking…are real-life problems this simple too? Eventually, during the course of the program, I spent time thinking about this question and began reading voraciously. This deep-dive enabled me to explore parametric, non-parametric forecasting models for bigger and incomplete datasets. As an outcome of all these readings, I realized two things: 1) these models are part of Machine Learning and 2) there is no one-size-fits-all model.
These were my small innings in Data Science which transitioned me to the R&D Lab of Mphasis.
At work, I started solving complex analytical problems alongside some very bright minds. This exposure enlightened me with some important pointers while attempting any ML-Based solutions i.e. Understanding the data, business requirements are idiosyncratic to the firm and industry as a whole and developing any ML-based solution with technological constraints is not as easy as it looks.
What excites me most about my job is that I get to work across multiple domains (Market Research, Supply Chain, Fintech, etc.) and multiple ML models (supervised and unsupervised learning). I believe this all-round exposure is important in the early stage of one’s Data Science career.
Data Scientists need to manage the balance between model complexity and business interpretability. While sophisticated models improve prediction power, it reduces interpretability for business decision-making. For example, building a sophisticated model to predict the best geographical location for the next brick-and-mortar store is one aspect but, the other aspect is to convert this into business context to help the leaders take big budgeting decisions. Handling this balance is a sure-shot skill I aspire to master.
I strongly believe in giving back to the society we live in. I actively research about major social challenges that our country is facing and try to understand and think about potential solutions. I had even designed data-driven models to evaluate the efficiency of State Governments in managing freshwater/sewage and proposed recommendations to improve their efficiency. I believe in learning for life and still keep looking for add-ons to this solution.
Anyone who knows me outside of work would surely tell you about my fitness enthusiasm and passion for poetry.
A data scientist who is also a ‘shayar’ by heart, now that’s a combo no one told you about.
Meet Ashish Bharti: Business Analyst, AI Researcher, and Poet