Summary
Overview
Work History
Education
Skills
Timeline
Generic
SUBHADIP CHAKRABORTY

SUBHADIP CHAKRABORTY

Bangalore

Summary

A results-driven data science and analytics professional with over 9 years of experience delivering impactful insights across marketing analytics, insurance pricing, life insurance, conduct analytics, product recommendation, automation, and capacity planning. Strong technical expertise in machine learning, predictive modeling, and data visualization, combined with a strategic understanding of business needs. Proven ability to translate complex data into actionable strategies that support decision-making for leading U.S.-based banking and insurance clients. Highly motivated, quick to learn, and passionate about using data to solve real-world problems.

Overview

9
9
years of professional experience

Work History

AVP, Decision Sciences

HSBC
Bangalore
06.2023 - Current
  • Created a compliance-driven anomaly detection model using AWS SageMaker to uncover mis-selling incidents within the insurance industry, reducing potential penalties, and boosting customer experience through timely intervention and actionable insights in Qlik Sense.
  • Built and deployed a next-best-product recommendation system for Singapore’s life insurance products, leveraging machine learning algorithms to personalize offerings and enhance the customer experience.
  • Led the end-to-end migration of reports, data, and Python scripts from AWS to GCP, collaborating with business and IT teams to ensure a smooth transition and driving $1.6M USD in estimated savings through operational optimization.
  • Collaborated with business users to address ad hoc requests, utilizing analytical tools to provide insights that supported key decision-making and improved business outcomes.

Senior Analytics Consultant

Wells Fargo
Bangalore
08.2021 - 06.2023
  • Led the development of predictive models and BI dashboards (Python, SQL, Tableau) to optimize call center operations across commercial banking LOBs, resulting in 60 FTEs saved and a ~2-minute reduction in customer wait times.
  • Developed an OCR-based information extraction pipeline in Python to process financial documents at scale, reducing manual effort by 200 hours per week, minimizing errors to nearly 0%, and ensuring compliance with regulatory standards.
  • Led recruitment and provided mentorship to interns and junior analysts, driving skill development in data science, coding best practices, and problem-solving to support team growth and project success.
  • Acted as the lead organizer for various organization-wide problem-solving initiatives and events, collaborating with stakeholders across departments to ensure smooth execution and high participation.

Consultant (Data Science)

EXL Services
Gurgaon
05.2019 - 08.2021
  • Developed GLM-based rating and pricing models for commercial auto insurance using Python, improving risk segmentation, and enabling underwriters to calculate more competitive and accurate premiums.
  • Heading a 6-member team in building an R (H2O)/Shiny-based ML pipeline to automate the full lifecycle of pricing models—monitoring, retraining, and refreshing—removing tool interdependencies, and significantly cutting manual overhead. Currently testing on Spectrum policies comprising 25 pricing models, with anticipated cost savings in the hundreds of thousands.
  • Helped modernize actuarial modeling by migrating GLM-based models from Emblem to Python (statsmodels, pandas, NumPy), enabling better model control, automation, and integration with advanced analytics pipelines.
  • Managed day-to-day project tracking through structured reporting and documentation using Excel, OneNote, and GitHub; delivered clear, client-ready presentations using PowerPoint to ensure alignment and transparency.

Analyst

Insos Research Pvt. Ltd.
Bangalore
07.2017 - 04.2019
  • Developed a machine learning model for a hotel client to predict frequent members at high risk of churn (i.e., unlikely to stay within 12 months of their last visit), enabling personalized retention offers. Leveraged logistic regression, decision trees, random forest, and XGBoost using Python (sklearn, pandas, numpy). The model helped drive targeted marketing efforts that contributed to an estimated $2 million increase in retained revenue.
  • Developed marketing mix models for clients across the restaurant, apparel, and pharmaceutical industries using R, enabling business stakeholders to understand the ROI of individual marketing channels. Insights from the models supported the reallocation of marketing budgets to high-performing channels, resulting in increased revenue and improved marketing efficiency.
  • Performed retail store segmentation using K-Means clustering in R to identify distinct store groups based on performance and customer behavior, enabling targeted marketing strategies, and operational optimization.
  • Conducted exploratory data analysis (EDA) on sales and marketing data using R, Excel, and PowerPoint to generate actionable insights. Created presentations that helped stakeholders better understand business performance, and validate data integrity for decision-making.
  • Analyzed the effectiveness and efficiency of each marketing tactic, and the influence of one tactic over another (HALO effect), to optimize marketing strategies and maximize ROI.
  • Calculated the marginal return on investment (MROI) and saturated point of each marketing activity to better optimize spending. Insights to optimize marketing spend and maximize returns.
  • Involved in creating ADS (Analytical Data Set) by pre-processing and collecting data from different data sources using SQL.nsights and project findings to stakeholders

Assistant Technician

Company 1
Kolkata
12.2015 - 02.2017
  • Maintaining daily/weekly/monthly reports of all Head-end on channel list as per bouquet of digital, package list of respective Head-end, STM down time & UP time reports and sharing the same to high level management and HO
  • Configuration of RF frequency and new channels

Education

PGDM - AI & Machine Learning

Great Lakes Institute
01.2022

PGDM - Big Data Analytics

IISWBM (University of Calcutta)
01.2017

Bachelor of Computer Applications (H) -

Techno India (WBUT)
01.2015

Skills

  • Python programming
  • SQL (T-SQL, BigQuery)
  • R Studio
  • AWS (SageMaker)
  • GCP (BigQuery)
  • Advanced Excel
  • PowerPoint
  • Statistics
  • Machine learning
  • Random Forest
  • XGB
  • Decision Tree
  • Extra Tree
  • Regression
  • Logistics
  • Classification
  • Clustering
  • Deep learning
  • Neural network
  • Market Mix Modeling
  • Text mining
  • Customer segmentation
  • Business Intelligence
  • Dashboard creation
  • Time series analysis
  • Predictive modeling
  • Project Management (Git, JIRA, Confluence)

Timeline

AVP, Decision Sciences

HSBC
06.2023 - Current

Senior Analytics Consultant

Wells Fargo
08.2021 - 06.2023

Consultant (Data Science)

EXL Services
05.2019 - 08.2021

Analyst

Insos Research Pvt. Ltd.
07.2017 - 04.2019

Assistant Technician

Company 1
12.2015 - 02.2017

PGDM - AI & Machine Learning

Great Lakes Institute

PGDM - Big Data Analytics

IISWBM (University of Calcutta)

Bachelor of Computer Applications (H) -

Techno India (WBUT)

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