Piramal Capital Housing Finance - Data Scientist Lead/AVP - Risk Modeling - IIT

ABOUT US

Piramal Capital & Housing Finance (PCHF), wholly owned subsidiary of Piramal Enterprises Limited (the flagship company of Piramal Group), is registered as a housing finance company with National Housing Bank (NHB) and engaged in various financial services businesses. It provides both wholesale and retail funding opportunities across sectors. In real estate, the platform provides housing finance and other financing solutions across the entire capital stack ranging from early stage private equity, structured debt, senior secured debt, construction finance and flexi lease rental discounting. Hospitality sector financing is a recent foray of PCHF. Here we are providing financing solutions to hotels which will be operated by branded players in established and emerging markets.

The wholesale business in non-real estate sector includes separate verticals - Corporate Finance Group (CFG) and Emerging Corporate Lending (ECL). CFG provides customized funding solutions to companies across sectors such as infrastructure, renewable energy, roads, industrials, auto components etc. while ECL focuses on lending towards Small and Medium Enterprises (SMEs).

PCHF through its group companies provides customized strategies for institutional and retail investors such as Mumbai Redevelopment Fund focused on slum rehabilitation and Apartment Fund focused on bulk buying individual units (Through Piramal Fund Management) and strategic partnerships with leading global pension funds such as CPPIB, APG and Ivanhoe Cambridge.

Data Scientist

BUSINESS: Piramal Financial Services

DEPARTMENT: BIU

LOCATION: Bangalore/ Kurla

BAND: 3A

QUALIFICATION:

Graduate

EXPERIENCE:

- Graduate from Engineering, MBA, Maths stream from IIT's only

- 5-8 years of relevant experience preferably in Financial Services Industry

- >=4 years of experience in analytics, ML and AI

KEY ROLES/RESPONSIBILITIES:

- Build Acquisition Scorecard Models

- Build Behaviour Scorecard Models

- Enhance Credit Underwriting Framework

- Strengthen Digital Lending and Digital Underwriting Framework

- Build Collection/ Recovery Models

- Create Digital Collection Framework

- Create Fraud Detection Models

- Build Fraud Triggers from various sources of data

- Monitor and Track Risk, Fraud and Collection related metrics to drive Business outcome