EarlySalary.com - Manager - Risk Analytics

EarlySalary is an instant line of credit to young working Indian. EalySalary is a pioneer in introducing instant loans & salary advances and has disbursed over Rs.2,000Cr worth of loans on its platform and currently disbursed nearly 100,000 loans a month. EarlySalary has raised multiple arounds of investment from global investors including Eight Roads (Fidelity) Ventures & Chiratae (IDG) Ventures and is considered one of the fastest growing FinTech start-ups in India. With a clear focus to disrupt the finance and banking domain, EarlySalary has built a strong team focused on build Technology, mobile platform, Risk & AI/ML models to better decisioning and real time lending. As a full stack lender we manage both sides of the business building better technology and products for powering our lending platform and build ML models for better risk mitigation and giving real time decision to our customers.

Our ML & Risk Analytics Stack & Practice is focused on building better Risk Score Card & building high amount automation. EarlySalary is considered one of the fastest & most automated lender in the Industry.

ROLE & RESPONSIBILITIES

- The successful candidate will be responsible for developing, analyzing and executing ideas and initiatives designed to achieve business growth and loss mitigation goals.

The core responsibilities will include:

- Hands on experience in building and deploying risk related scorecards (like application, behavior, collectionsetc. preferably lending business) using some of the latest machine learning models.

- Has worked on modeling projects/unstructured problems, look at providing solutions that go beyond traditional methods.

- Using advanced machine learning technologies and new data sources. Develop next-gen modeling capabilities to deliver best in class predictive modeling solutions.

- Apply innovative analytical techniques to customer and transaction data to build risk mitigation strategies and processes.

- Liaising internally with risk managers, including explaining model outputs, performing ad-hoc analysis and answering technical or background questions on the models and requirements.

- To define, analyze, implement, and monitor credit risk strategies. Must have capability to clearly communicate analyses.

- Must be able to effectively provide updates and communicate key initiatives to senior management.

- Must have hands on expertise in developing and managing scoring models

Qualifications

- Degree in Statistics, Physics, Applied Mathematics, Operations Research, Econometrics, Engineering or other quantitative discipline

- 3-5 years of work experience, with 1+ years of experience in risk analytics scorecard

- Ability to work with large amount of data (size in TBs)

- Extensive coursework / experience in quantitative analysis & statistical modeling in consumer credit risk will be a plus.

- Understanding of consumer credit risk management, Credit Profit & Loss Drivers preferred

- Excellent written and verbal communication skills, and be able to prepare presentations for executive level audience and familiarity with Power Point, Excel, Visual Basic

- Prior experience in banking or nbfc (credit cards or personal loan) will be a plus

- Detailed-oriented, high level of intellectual curiosity and strong sense of ownership.

- Demonstrated ability to multi-task effectively and work against tight deadlines

- Good business acumen and the ability to connect analytics with business decisions

Technical capability

- Extensive experience in python (or similar tools) to build ML models

- Hands on experience with SQL (or similar structured on non-structured databases)