Abhik

Abhik Hazra

Data Science & Analytics

Summary

I’m a data science professional with ~7.5 years of experience working across large global organizations, including Deloitte, Bank of America (US market), and HSBC (UK market). My work spans risk, fraud, and sales analytics, with a strong focus on building interpretable machine learning models and translating data into decisions that matter.

I’ve led end-to-end analytics initiatives – from exploratory analysis and feature engineering to model development, monitoring, and stakeholder communication. I enjoy working at the intersection of data, business context, and long-term strategy.

Experience

Deloitte — Manager, Lead Data Scientist

Oct 2025 – Present

  • Leading a team of 5-6 data scientists on machine learning model development in the insurance domain, covering risk, sales, and fraud use cases
  • Involved in team hiring, expansion, and capability building in ML and AI
  • Reviewing and improving ML/AI processes across multiple client engagements
  • Building Model Validation pipelines using Agentic AI and RAG-based frameworks.
  • Tech stack: Python, SQL, Google Cloud Platform (GCP)

Bank of America — Manager, Risk Data Science

Nov 2020 – Oct 2025

  • Designed and deployed machine learning models (GBM, Random Forest, XGBoost, Logistic Regression) to detect risk and identify loss drivers, generating multi-million dollar monthly savings
  • Led a large-scale U.S. population network analysis to map social connections and identify key influencers, contributing to significant annual cost savings
  • Developed interpretable ML frameworks (including RuleFit) to tag high-risk populations and support regulatory-aligned decision-making
  • Owned the full model lifecycle: EDA, feature engineering, model tuning, validation, and compliance alignment
  • Built and maintained automated monitoring pipelines using PSI and CSI to detect data drift and trigger recalibration
  • Partnered with senior leadership to define a 3–5 year roadmap for data-driven initiatives, prioritizing projects with strong ROI.
  • Designed executive dashboards and automated alerts for leadership visibility
  • Supported early-stage migration from relational databases to graph databases and collaborated on scalable deployment workflows
  • Explored and implemented modern ML platforms, including AWS SageMaker and H2O Driverless AI, reducing model development time by 15–20%
  • Interviewed and onboarded 150+ candidates and supported team expansion initiatives
  • Tools: Python, SQL, PySpark, Hive, TigerGraph, H2O Driverless AI

HSBC — Decision Sciences Analyst

Jun 2018 – Oct 2020

  • Supported the development of credit card application models for the UK market using machine learning techniques such as neural networks and random forests
  • Introduced graph databases and network analysis to identify large-scale fraud rings
  • Built SAS pipelines to quantify fraud volumes across portfolios for the first time, uncovering significant loss exposure
  • Designed risk strategies for unsecured lending products based on scorecard outputs
  • Developed an R Shiny application for fraud detection using graph-based label propagation methods
  • Automated portfolio monitoring dashboards and reporting, reducing runtime by ~80%
  • Conducted R programming training sessions for 30+ associates during the transition to R-based analytics
  • Evaluated third-party vendor models (Experian, Visa) through cost–benefit and performance analysis
  • Built fraud application models for partner brands within the HSBC ecosystem

Education

M.Sc. in Applied Economics (2016-2018)
Presidency University, Kolkata

B.Sc. in Economics (2013-2016)
Presidency University, Kolkata

Internships

Institute of Development Studies, Kolkata — Research Intern

May 2014 – Jul 2014

  • Analyzed socio-economic datasets for minority-concentrated villages in West Bengal
  • Conducted regression analysis to study relationships between education, income, and resource access
  • Produced statistical reports supporting policy-oriented research

Skills

Technical
Python, R, SAS, Advanced SQL, Hadoop, Spark, Machine Learning (XGBoost, H2O), Deep Learning, NLP, Data Analysis, Tableau, Risk Modeling

Professional
Analytical Thinking, Stakeholder Communication, Leadership, Team Building, Problem Framing, Adaptability

Awards & Recognition

  • Team Star Award – HSBC, for leadership and data-driven innovation
  • Commendation from HSBC UK CRO for identifying large-scale fraud rings and preventing significant losses
  • Multiple Gold and Silver Awards – Bank of America, for impactful analytics and risk management initiatives

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