About EarlySalary:
EarlySalary is an instant line of credit to young working Indians. EarlySalary is a pioneer in introducing instant loans & salary advances and has disbursed over Rs.4,000Cr worth of loans on its platform and currently disbursed nearly 100,000 loans a month and is considered one of the largest Digital Consumer FinTech Lender in the country.
EarlySalary is a series C funded start-up and has raised multiple rounds 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 decisions to our customers.
Our ML & Risk Analytics Stack & Practice is focused on building a better Risk Score Card & building a high amount of automation. EarlySalary is considered one of the fastest & most automated lenders in the Industry.
Job Title: Sr. Data Analyst - Collection Analytics
Experience : 2-5 Years
Job location : Pune
Technical capability :
- Hands-on experience with SQL (or similarly structured on the non-structured database)- (Data Extraction, Joints, Window functions, Subquery)
- Hands-on experience with Tableau or any reporting tool (Quicksight is used)
- Experience in python (R Python) will be an added advantage
- Pandas- library used for transformation of tabular data (Intermediate experience)
ROLE & RESPONSIBILITIES:
- The successful candidate will be responsible for developing, analysing, and executing ideas and initiatives.
- Use sophisticated analytical techniques to solve a business problem specific towards Collections &Recovery and build collections strategy around the portfolio.
- To develop customer risk strategies, segmentation and profiles, using data science based tools and techniques for driving collections & recovery management.
- To work closely with risk and underwriting team for improvement in collections and closing the feedback loop on the delinquent cases.
- Design modules for advanced score card development and analytical tools and understand the impact of deployed models
Preference and Experience :
- 2+ years of experience in an analytical capacity required in lending domain
- Ability to work with a large amount of data (size in TB- s)
- Extensive coursework/experience in quantitative analysis & statistical modelling in consumer credit risk will be a plus.
- Exposure of consumer credit risk management, Credit Profit & Loss Drivers preferred
- 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
- Good Problem solving and Structured thinking/ Data interpretation
Academic qualifications: Degree in Statistics, Physics, Applied Mathematics, Operations Research, Econometrics, Engineering, or another quantitative discipline
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