Every company will be a fintech company
Ever since we began our journey in 2013, our aim has been to enable credit for every possible earning individual. Like payments, which have become digital, embedded & ubiquitous in the last 8 years, credit too will become a ubiquitous instrument for a consumer/business owner to transact for various purchases whether it is a vanilla Term Loan to consumer financing to working capital finance. And we are at the forefront of this shift.
- We are one of the top-rated AI companies in India built credit scores, and alternate data products using multiple data sources, and operate as SAAS for 50+ clients across the banking and tech industry.
- We are technology first, customer first and build products that help us give asymmetric scale
- We launched embedded credit in 2020 under the brand name Prefr where we deeply embed our solution within a large online distribution platform at the time of the transaction for consumers via Personal Loan/Consumer Loan
- We have embedded our solution with over 30 partners
- Our current annualized disbursals as of FY 2023 stand at $200mn
- Our team comes from a variety of backgrounds: Experts from NBFC, Bureaus, Banking, Technology, ex-entrepreneurs, co-located, PAN-India, diverse.
Key Responsibilities:
- Develop machine learning models that drive actionable insights to support business decisions.
- Working with large and complex datasets from various internal sources to generate insights.
- Develop frameworks for pre-approval strategies for new and within-funnel users. Monitor funnel efficiencies and take actions to further improve them.
- Explore and evaluate potential alternate data sources for incremental value in pre-approval programs.
- Develop and implement propensity models to predict customer behavior and preferences.
Qualifications:
- Bachelor's or Master's degree in a quantitative field (e.g., Computer Science, Statistics, or related field)
- 3+ years of hands-on experience in data science and analytics roles.
- Strong proficiency in programming languages such as Python or R.
- Demonstrated experience with machine learning algorithms and statistical modeling techniques.
- Excellent problem-solving skills and the ability to think analytically.
- Effective communication skills and the ability to work collaboratively in a team environment.
- Good business acumen with a strong ability to solve business problems through data-driven quantitative methodologies
Preferred Skills:
- Experience with big data technologies (e.g., Spark).
- Industry-specific domain knowledge, particularly in lending or financial services.
- Experience with unstructured data handling
- Understanding of credit bureaus and non-traditional data providers will be a plus
