Rahul Pandey
Summary
Accomplished Data Scientist with expertise in risk analytics and fraud detection, previously at Bank OZK. Developed a KRI analytics platform, automating workflows and saving $24K+ annually per user. Proficient in Python and skilled in stakeholder communication, driving impactful data-driven decisions across organizations.
Overview
7
7
years of professional experience
Work History
Data Scientist
Bank OZK
12.2024 - Current
- Developed enterprise-wide Risk Appetite & KRI analytics platform for executive-to-loan-level insights.
- Replaced external Watchtower system with in-house ERM solution, automating data pipelines and reporting workflows, resulting in $24K+ annual savings per user.
- Designed early-warning credit risk framework to identify portfolio deterioration signals.
- Automated sourcing and NLP-based scoring of appraisal reports, eliminating over 10 hours of manual review weekly.
- Supported deployment and execution of Internal Loss Default (ILD) challenger model, collaborating with validation and governance teams on SHAP explainability.
Data Scientist
The Hanover Insurance Group
01.2023 - 09.2023
- Built a flag-feature analytics framework for underwriting risk assessment across 300K+ commercial policies.
- Applied XGBoost and GLM models with NAICS segmentation, driving a 37% reduction in large-loss exposure.
- Developed NLP pipelines using BERT transformers to automate claim cause classification, reducing manual effort by 16%.
- Presented analytics solutions to business leadership, securing approval for further deployment.
Data Scientist
Capgemini Technology Services (Client: HSBC)
10.2018 - 01.2022
- Redeveloped a Risk-as-a-Service (RaaS) fraud detection platform for Middle East banking clients, contributing $3M in Q4 revenue retention.
- Built ML pipelines on AWS to predict fraudulent transactions and account takeovers, achieving a 15% Gini uplift.
- Migrated complex SAP BO reporting to Tableau, reducing costs by 15% and improving usability across teams.
Education
M.S. - Data Science
Northeastern University
Boston, MASkills
- Risk analytics expertise
- Fraud detection techniques
- KRI framework development
- Predictive modeling systems
- Governance of models
- Explainable AI methodologies
- XGBoost and generalized linear models
- Classification and regression analysis
- NLP technologies (BERT, Transformers)
- Time series forecasting methods
- A/B testing strategies
- Proficient in Python
- SQL proficiency for data handling
- Snowflake for data storage solutions
- Airflow for workflow management
- Docker for application deployment
- AWS cloud infrastructure expertise
- Azure cloud services knowledge
- Feature engineering practices in data science
- ETL process design and implementation
- Power BI for business intelligence reporting
- Tableau for interactive dashboards
Core Skills
Credit Risk Analytics, Fraud Detection, Risk Appetite & KRI Frameworks, Early Warning Systems, Model Governance, Explainable AI (SHAP), XGBoost, GLM, Classification & Regression, NLP (BERT, Transformers), Time Series, A/B Testing, Python, SQL, Snowflake, Airflow, Docker, AWS, Azure, Feature Engineering, ETL Pipelines, Power BI, Tableau, Executive Dashboards
Timeline
Data Scientist
Bank OZK
12.2024 - Current
Data Scientist
The Hanover Insurance Group
01.2023 - 09.2023
Data Scientist
Capgemini Technology Services (Client: HSBC)
10.2018 - 01.2022
M.S. - Data Science
Northeastern University