Moneyview is a leading fintech company headquartered in Bengaluru. The company provides financial services ranging from Loans, UPI, Smart Pay, Investment products & Credit Reports. Our easy-to-use App makes the documentation process simple, providing financial services within a few minutes! Moneyview is 10 yrs old; Series E funded by marquee investors like Accel, Tiger Global, Accel, and Ribbit Capital, and is currently pegged as a Unicorn. Moneyview is also a founding member of DLAI- Digital Lenders Association of India- a widely recognized body for Fintech players in India.

Experience: 2-5 Years

Location: Bangalore

Commitment: Full-Time

Job Description: (Mandate Skills)

What we are looking for:

Data Scientist preferably from financial services, large banks/MNCs.

• Strong background in business analysis (consumer/business strategy, financial products, pricing, etc.) with very strong data analysis (Sql, excel, etc,) experience
• Strong understanding of how to structure analysis and to solve real world business problems.
• Ability to identify key drivers of business and create KPIs/modeling solutions for the same,
• Expertise in end-to-end model development and model lifecycle management (develop, deploy, monitor) is preferred
• Exposure/Experience in developing Machine Learning models using various algorithms (logistic/linear, Random Forest. Xgboost ,etc)
• Hands on experience in R or Python is must
• Exposure to unstructured data analytics and big data handling is a plus
• Good business understanding of fintech/personal lending space is preferred

Responsibilities:

You'll work closely with the Product and Risk Team to:

• Define, design and deliver solutions using data science/analytics in fast paced environment
• Evaluate and apply machine learning algorithms to build variety of data science models particularly in credit risk/unsecured lending domain but not limited to
• Complete ownership including but not limited to identifying model development approaches, building ML models, evaluation, cost benefit analysis, exploration of new data sources, implementation and monitoring of developed models.
• Working closely with the engineering team for deployment of models and infrastructure development.