Job Description

About Us :

Liquiloans is a P2P (peer-to-peer) lending platform that caters to both borrowers and investors. P2P Lending is a licensed and regulated industry by the RBI. Our investors enjoy safe and steady returns. It's not crypto, it's not rapid growth. Our borrowers enjoy easy to pay EMI solutions for their purchases of goods and services. It's more like working hedonistically towards self improvement. We intend to become the best debt investment product out there for all Indians. We're four years old and 200+ members strong!

Our organization is an early stage well-capitalized NBFC-P2P with a vision to build an easy to use financial platform serving millions of customers in India. Our goal is to allow borrowers to get loans at interest rates cheaper than a bank and enable every lender to give loans to creditworthy individuals in a safe and legal manner. We intend to build a dynamic, completely tech enabled, loan exchange platform where individuals can lend money to other individuals within minutes. We plan to integrate the new age data driven lending strategies and come up with an end to end, easy to use, online spread of financial products and services. Ours would be a one stop destination for all our users, from providing credit facilities to offering investment opportunities. We aspire to develop India's one of a kind, highly liquid interface where an individual can invest, render and take exposure against existing credit employed within minutes!

Role : Data Scientist

1. The ideal candidate for this role should have a thorough hands-on grounding in Data Science libraries, predictive modelling and programming

2. The ideal candidate should be able to evaluate several options for variety of prediction tasks independently and turn business requirements into modelling recommendations.

This will involve :

a. Be expert at data transformation

b. Brainstorming along the relevant modelling criterion

c. Model creation/evaluation

3. The candidate should possess :

a. Thorough knowledge of Data Science libraries - Numpy, Scipy, Pandas, Scikit-learn

b. Familiarity with wide array of generally used models in regression/classification - such as Decision Trees, Random Forests, logistic regression, linear/multivariate regression.

c. Knowledge and implementation skills of both - supervised/unsupervised learning.

4. Strong knowledge in programming

5. The candidate should be able to collaborate effectively with a wide team of business analysis and senior business stakeholders.

Funding : Raised Series A funding from Matrix Partners

Education Qualification : Graduate/Post-graduation in Engineering/ Computer Science/ Mathematics.

Programming Stack : Python

Experience : 2-3 years