Gaurav Singh Email & Phone Number

Raleigh, Nc, Us

Santa Clara, Ca, Us

Santa Clara, Ca, Us

In my current role at Tiger Analytics, I lead data science and analytics consulting engagements in banking finance industry . My team of 35+ members bring in wide variety of expertise ranging from data science, data engineering, analytics and BI. Some of my primary work area is around:Product Analytics, Alternate data for lending, fairness of the model, Buy Now Pay Later analytics, credit risk modeling and validation, building data assets and products, Climate risk evaluation, Generative AI/LLM Ops use cases for banking

Cary, Nc, Us

Collection AI:Helped build collection AI solution that streamlines collection and recovery process for lenders. Some key components of the solution are:-- Early Warning system: This system flags the consumer who have not yet defaulted but can potentially default in coming months.--Behavior profile: This system combines the behavior attributes of consumers (like self-cure, repeat offenders, low MOB troubles etc ) with credit profile.--Optimized Channel decisions- This component enables user to build cost effective strategies tailored for consumers based on their propensity to respond to a channel, and amount due.

Cary, Nc, Us

Credit Risk Analytics:- Helped over dozen of financial institutions build and implement expected credit loss forecasting models for variety of portfolios (Mortgage, PL, Auto finance, HELOC, credit card etc). The solution helped banks, farm credits and credit unions to remain compliant with CECL regulation. Marketing Analytics:--Helped leading retailers (The North Face, Vans) build an omnichannel platform that provides 360 degree view of consumers. Some key components of the solution were: propensity scores, customer life time value models, persona and activity model, channel preference model, reverse price sensitive model, weather proactive vs reactive models, next best action models etc. The solution helped with targeted campaigns leading to an increase of MROI by 35% and improvement of customer response rate on average by 3.5 times. Further, I led the design of experiments (test vs control) to measure the effectiveness of marketing campaign, Incremental dollar value , performance of the models.--Built market mix models (GL mixed model) to explain how sales are attributed to marketing spends. Built a recommender system that recommends optimal spends and also enables marketing managers to perform 'what if' analysis.

Cary, Nc, Us

Pension fund risk management (NC Treasury)• Helped NC pension fund build a multi-asset class risk management tool that enables portfolio managers to better assess portfolio performance and quantify/manage risk• Over dozens of different data sources at different were employed, combined • The tool allowed the users to forecast asset returns, build allocation strategies and optimize based on expected cash flow along with daily, monthly, quarterly reporting of financial measures.Modelling techniques• Bayesian vector autoregressive (BVAR) model for economic forecasts• Neilson Segal model for yield curve forecasting• Asset class return modeling using economic scenarios • Cash flow projection as part of ALM framework• Black Litterman optimization to optimize allocation strategies

Cary, Nc, Us

Financial risk modeling and research

credit Risk model development and validation

Kanpur, Up, In

Kanpur, Up, In

Kanpur, Up, In

Masters In Statistics, Iit Kanpur

Bsc (Hons.), Statistics

Education record