I currently work at Unum - a Fortune 500 company - leading a team of Data Scientists, Data Engineers and Business Intelligence developers to deliver data-driven solutions for the enterprise. My expertise lies in translating complex business problems into actionable data science and analytics strategies, with a focus on driving measurable impact.
I have a strong quantitative background with a Master's Degree in Physics from IIT Kharagpur and 11+ years of experience in data science, analytics, and machine learning. I have been in people management and leadership roles for over 7 years, mentoring and guiding teams to achieve their full potential.
Background
Education
Integrated B.Sc. + M.Sc. Physics
2009–2014
IIT Kharagpur
AWS Certified AI Practitioner
2025
Amazon Web Services
Perplexity AI Business Fellowship
2025
Perplexity
Micromasters in Data Science
In Progress
MITx
Work Experience
Director, Data Science & Analytics
2020–Present
Unum
Consulting Manager
2017–2020
EXL Analytics
Consulting Data Analyst
2014–2017
EXL Analytics
Core Competencies
Technical Expertise
- AI/ML: Agentic AI, RL, XGBoost, GLM (Generalized Linear Models), Time Series Forecasting, Backpropagation, SVM
- Data Engineering: SQL, Python, SAS
- Cloud Platforms: AWS, Azure, Databricks
- Business Intelligence: Power BI, Tableau
Leadership Strengths
- Team Leadership: Recruiting, Coaching, Mentoring diverse teams
- Strategic Planning: Vision, Roadmap Development, Prioritization, Execution
- Business Impact: Data Driven Decision Making, ROI, Business Case Development
- Stakeholder Management: Securing stakeholder alignment for new initiatives
Business Impact
Analytics Leadership for Digital Transformation
I served as the analytics lead for a $20M digital transformation initiative within Claims Operations. I translated complex business goals into quantifiable metrics, followed by design, implementation, and reporting on those metrics.
Impact:
Data driven progress tracking and accurate performance measurement for a reliable transformation process.
A/B Testing for Customer Wellness
I designed and implemented A/B testing initiatives for a 2M+ Customer Wellness program. I was responsible for leading the entire study, which included designing the key measurements, determining the required participant volume, establishing the measurement period, and reporting results to guide critical business decisions over a multi-year period.
Impact:
The A/B tests provide the foundation for future program enhancement and scaling with $1B+ potential impact.
ML Modeling for Customer Risk Segmentation
I led the development of machine learning models to enhance customer risk segmentation. I led the process from start to finish—translating actuarial problems into predictive modeling formulations, engineering data pipelines, and guiding the development of the ML models, including feature engineering, hyperparameter tuning, and model evaluation using multi-variate SHAP values for interpretation.
Impact:
The insights from these models directly informed our financial assumptions, which in turn influenced a balance sheet exceeding $15B.
Data Engineering Pipeline Management
I lead the management of a large-scale data pipeline consolidating customer attributes from hundreds of SQL tables to create 10 well-curated datasets used for financial modeling. The pipeline is a mix of fully-automated SQL Stored Procedures and a semi-automated Python and SQL codebase, which produces large datasets over 100GB in size.
Impact:
Accurate and timely availability of data that's considered one of the most critical data infrastructures within the enterprise.
Analytics Transformation
I led a multi-year transformation of our team's analytics capabilities. This involved working closely with various analytics stakeholders to synthesize their analytics requirements, translating those into specific metrics, architecting the Business Intelligence Schema, and then leading the development of the data engineering and visualization components.
Impact:
This transformation has enabled the team to deliver reliable sources of truth for key metrics, and has significantly improved the team's ability to provide data-driven insights and recommendations on a real time basis.
Forecasting and Capacity Planning
I implemented a capacity planning solution for an organization of over 200 full-time employees. I used time series forecasting to predict future case volumes for more than 10 lines of business and integrated these forecasts with FTE unit metrics to project staffing needs.
Impact:
This solution enabled the organization to make informed decisions about staffing and resource allocation, ensuring that we are well-prepared to meet future demands.
Personal Projects
🌱 Nurture My Plants
A web application that uses LLM technology to identify plants from uploaded photos and provide personalized care plans. Built to help my wife, a passionate newbie gardener (among many other amazing things), learn proper plant care techniques and identify her growing collection.
Impact:
Empowering home gardeners with AI-powered plant identification and personalized care guidance.
Next.js
Anthropic API
Vercel
Image Processing