As we take on more customers and unique challenges, we are looking for a Staff Data Scientist who can help optimize performance of our deployed product models. Come join a team of creative technical experts who collaborate with customers to ensure their success with OfferFit!

In Short

Take a leading role in the optimization and troubleshooting of live Reinforcement Learning and Causal ML models driving OfferFit's marketing campaign use cases.
Analyze and improve OfferFit's Reinforcement Learning and Causal ML algorithms in collaboration with the Applied ML engineering team that develops our ML pipeline.
Create new custom diagnostic tests and analyses to support OfferFit's Reinforcement Learning and Causal ML algorithms.

Requirements

Experience: 5+ years in industry Data Science and Machine Learning with an emphasis on live prediction applications in the consumer space (churn, fraud, etc.)
Scientific Problem Solver: You think deeply about the data in your ML problem and rigorously analyze the impact of your interventions.
Calm under pressure: Systematically and efficiently determine the root causes of poor performance and deduce model issues under tight time lines and high client expectations.
Solid coder: you write clean, well documented code; you care about good design.
Tinkerer: you regularly explore and learn new technologies and methods
Entrepreneurial: you proactively identify opportunities and risks, work around obstacles, and always seek creative ways to improve processes and outcomes
Structured and organized: you can structure a plan, align stakeholders, and see it through to execution
Clear communicator: you are able to express yourself clearly and persuasively, both in writing and verbally

Benefits

Generous PTO (starting at 25 days PTO per year) and Parental Leave policy (12 weeks paid)
100% remote work environment with flexible hours
Quarterly gatherings where we meet in person in a different city to work together, bond as a team and celebrate our progress
Weekly team events (lunch and learns, trivia, virtual escape rooms, town hall and team health “barometer” meetings)
Ability to learn and develop under an experienced leadership team (ex-Amazon, McKinsey, BCG, and IBM, among others) who are focused on building a talented, diverse, and inclusive team
Dedication to building a strong culture (e.g., team resource groups, weekly recognitions, major life event celebrations, mental health/sustainability days off, etc)