Lead Data Scientist

Advanced degree in data science, statistics, computer science, or related field.
5+ years of experience doing data science (modeling + analysis)
Proficiency in Python and in-depth understanding of SQL
Competent in machine learning principles and techniques
Experience in python, using industry standard modeling toolkits like sklearn, jupyterlab, pandas, matplotlib, statsmodels, etc.
Experience in writing complex SQL queries and the ability to put together multiple data sources together
Ability to get the train data, train the model, do hyper parameter tuning, perform validation, run the A/B test, do performance monitoring and model monitoring
Experience building classification and prediction models, testing them in a startup environment and iterating to improve their models.
Ability to work effectively and communicate ideas/code clearly in a cross functional team environment (Engineering, Product and Business teams)

Build, test and roll out new underwriting and risk models to understand the risk of our customer base and improve access for our prospective customers by allowing us to take more calculated risks.
You’ll have ownership of the full modeling lifecycle and get to carry your changes all the way through to our decision process, getting to realize every bit of impact along the way.
Build, test and roll out other customer related models (such as Churn propensity and LTV prediction) which help us analyze and optimize our marketing and retention efforts.
Monitor the performance of the models in production and take appropriate actions when necessary
Analyze how our customer base is shifting as we grow and pinpoint areas we can improve.
Help our existing engineering and business teams track their goals, supporting the BI function from time to time to time with ad-hoc data analytics

ML model deployment in production experience is a plus
Technical presentation skills is a plus
Experience working in B2C, marketplace, lending, or subscription oriented business is a plus