Jul 2021 – Feb 2024 · 2 yrs 7 mos · Bengaluru, Karnataka, India

• Hands-on leader managing a team of data scientists and software engineers
• Building ML opportunity identification platform which has led to multi million dollar revenue impact. These models recommend transaction opportunities spanning multiple IB products/regions e.g. M&A Sell-Side, ECM/DCM, Private Markets (IPO/M&A) etc
• Build ESG analytics toolkit for client advisory e.g. carbon emissions profiling, investor analytics, cost of carbon, activism analytics etc
• Recommendation engine to show relevant thematic content to clients
• PDF parsing and table extraction from allocation documents (relationship lending/DCM)
• Redesigned agency models for CCAR reporting
• Build a PSI RFP automation tool using custom RAG for Large Language Models
• Analytics for various client situations such as M&A, Activism etc
• Tech Stack: Python, AWS, Tableau

Jan 2019 – Jun 2021 · 2 yrs 5 mos · Bengaluru Area, India

• Implemented a classification model to predict whether the FX available in a fixed income portfolio should be converted to portfolio base currency to avoid currency risk. Models implemented: Logistic Regression, Random Forest, LightGBM
• Worked on statistical quantification of market herding bias in portfolios. Models used: Mixed effects model, Linear Regression
• Forecast offer spread for corporate bonds.
• Working on optimal trade execution strategy for high income trades using liquidity measure.
• Built a classification model to predict the hard to borrow stocks for sec-lending market. Models implemented: Logistic Regression, Random Forest, XGBoost
• Identification of impact of etf flows on stock characteristics such as returns, liquidity after controlling for systematic factors such as momentum, value etc. Models implemented: Quantile regression, Robust Regression
• Helped in building a default model for banks (for counter-party) using features suggested in Basel Norms. Model used: Balanced RF, Balanced Logistic Regression
• Other Initiatives:
• Predict the outflows flows in portfolios using market factors, customer trends etc
• Build a missing value imputation recommendation guide for data scientists
• Winner of Eureka Award for innovation
• Tech Stack: Python, R, SQL, Tableau, Snowflake, AWS

Nov 2017 – Jan 2019 · 1 yr 2 mos · Gurgaon, India

• Behavioral Finance: Developed algorithms to detect trading patterns/investment styles using trade diaries for fundamental equity Portfolio Managers
• Developing algorithms for operational and liquidity risk profiling. Building and enhancing factor risk models. Designed and implemented new exception framework which is used for regulatory reporting.
• Portfolio constraints classification for private investor business. Design new methodology to calculate tracking error
• Developed a recommendation algorithm for investment management documents using word embeddings to enhance the operational process
• Anomaly detection algorithm in expenses to forecast operational risk
• Tech Stack: R, Python, SQL, PySpark

Dec 2015 – Oct 2017 · 1 yr 10 mos · Noida Area, India

• R&D initiatives
• Developed signal processing and deep learning capability on EEG data to predict seizure. (Paper presented at international healthcare conference - IIM Ahmadabad).
• Developed claim fraud algorithm by association mining and clustering to identify wrong diagnoses, procedure bundling. This helped reduce fraud claims by ~5%
• Enhanced discovery capability of intranet search portal using NLP
• Predict claims with high risk of appeals in M&R space. This was replicated for other LOBs
• Project Delivery
• Built a dynamic network optimization algorithm to determine next best provider to meet CMS requirement of having atleast 90% member coverage for all specialties
• Predict ER visit for asthma patients using internal claims data supplemented by air pollutant, weather data etc (Paper presented in internal UHG conference)
• Predict providers with high chances of having an incorrect record. Model successfully utilized for campaigns with ~60% hit rate
• Tech Stack: R, Python, SQL, PySpark, Hive

Jun 2015 – Nov 2015 · 5 mos · Hyderabad Area, India

• Built a model for patient allocation in trials based on various constraints such as cost and time. Created a risk score algorithm to assess the performance of investigators in a clinical trial
• Tech Stack: R, Python, SQL

Aug 2014 – May 2015 · 9 mos · Gurgaon, India

• Developed promotion effectiveness algorithm for an Indian retailer. Built a dashboard to evaluate overall and promotion level impact
• Analyzed transaction data for a Thai Retail Chain, identified B2B and B2C transactions, and created recommendations by region which were delivered in form of Shiny App
• Performed segmentation for an Indonesian Telecom to understand customers’ needs/demands. Market basket and correlation analysis was used to bundle various packets for cross-sell
• Tech Stack: R, Python, SQL, Alteryx

Nov 2010 – Jul 2014 · 3 yrs 8 mos · Greater New York City Area

• Led the initiative to bring credit card submissions (50 TB) into HDFS. Performed UAT to ensure data sanctity. This assessment led to projects such as small merchant risk scanner& location based targeting
• Developed and implemented the Merchant Exposure Calculation (PIT) algorithm. Managed the development of Exposure Management Capability. Interacted with global business partners to build wireframe for the tool
• Worked directly with senior leadership to size two major initiatives: Transaction amount/Portfolio based Pricing and small merchant portfolio revamp using external data
• Enhance marketing strategy of a top credit card issuer by predicting customers’ channel affinity. Developed offer level customer segmentation using predictive modeling and assessed campaign performance
• Tech Stack: SAS, SQL, R