Money View - Senior Data Scientist

About the Company:

Moneyview is in the online/instant personal loan space, catering to the underserved segments, providing loans of up to 5L through a completely digital platform. Our unique IP assesses creditworthiness using multiple data sources and does not only rely on the bureau score, thus offering better approval rates and loan amounts. Our easy-to-use App makes the documentation process simple, providing the loan offer in less than 2 mins and disbursal within few minutes! The company has two products- Money View Loans and Money Manager. MVL App has over 10M+ downloads and is one of the few highest-rated apps in the category with 4.7 ratings. The company plans to expand into other financial products and provide a full suite of credit products. Moneyview is around 9yrs old; Series E funded by marquee investors like Accel, Tiger Global, Accel, and Ribbit Capital, and is currently valued at $900 million. We provide loans in partnership with top NBFCs and Banks. Moneyview is also a founding member of DLAI- Digital lenders association of India a widely recognized body for Fintech players in India.

What are we 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 a 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 approach, building ML models, evaluation, cost benefit analysis, exploration of new data sources, implementation, and monitoring of developed models.

- Working closely with engineering team for deployment of models and infrastructure development.