Staff Data Scientist - Remote

Overview

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)