Data Scientist - Remote
San Francisco, CA
Credit – Data Science /
Full-time /
Remote
Empower is a high-growth financial technology company on a mission to expand access to fair credit to give anyone in the world the opportunity to improve their financial security and mobility. We dream up and launch one-of-a-kind features that help our members get money instantly whenever they need it, save for the future, and rewrite their financial story. Our members see Empower Cash Advance as a life-saver, Empower Automatic Savings as a game-changer, and the new Empower Thrive line of credit (currently in beta, launching soon) as a lifeline to low-cost borrowing and the only practical path to building good credit.
Empower is backed by Sequoia Capital, Blisce, and Icon Ventures. Inc. ranked Empower #55 in the 2022 Inc. 5000 list of the fastest-growing private companies in the US. Fast Company recognized Empower Thrive in their 2022 list of the Next Big Things in Tech.
Want to make a difference in someone’s journey to better credit? Let’s go.
Our data scientists are responsible for the entire model development process from conception with stakeholders, creation of model pipelines, technical development, deployment, and partnership with the credit, product, and finance teams to make business decisions.
The ideal candidate is passionate about using data and models to drive business growth and help customers improve their financial situations. This individual will own creating and improving credit risk models to help the business decrease loss rates and increase approval rates. They will also need to partner with product, tech, and finance teams to build out solutions that drive value for Empower and our customers. The right person for this role is someone who shines while solving complex problems and is comfortable with a wide variety of technical tools.
What you'll drive
- Grow user base and increase retention through machine learning and analytics
- Build machine learning models with large scale data sets to address business priorities
- Design and influence strategies on underwriting, marketing, fraud and customer experience
- Work closely with our engineering team as you implement models in production
- Collaborate effectively with operations and product to ensure the work fits into the broader strategy and business context
- Develop data standards and analytics pipelines to facilitate current and future analysis
To thrive, you’ll need to have
- BS degree in engineering, computer science, finance or mathematics
- 2+ years industry experience in data mining, machine learning, statistical analysis, and/or predictive modeling
- Deep understanding of statistics and machine learning techniques, including regression, classification, clustering and optimization Experience building predictive models from scratch
- Strong programming skills (Python preferred) with intermediate to advanced knowledge of SQL
- Demonstrable experience with ML packages: scikit-learn, LightGBM, XGBoost, SparkML, etc.
- Knowledge in deep learning and experience with DL toolkits (Tensorflow, Keras, PyTorch) is preferred though not required
- Comfort working with a variety of cross functional partners in tech, product, credit, and business
- Strong and structured approach to problem solving and ability to use of frameworks to communicate complex topics in an effective manner
Preferred Qualifications
- MS or PhD preferred
- At least one year at a bank or FinTech working in data science or credit analytics is a plus
- Experience in cloud computing (AWS, Azure, etc.) is a plus
At Empower, we hire for people that push themselves to understand others and seek out ways to challenge their personal assumptions. Our hope is that by fostering such an environment, we strengthen our business and relationships by putting people first. We are committed to building a diverse, inclusive, and equitable workspace where everyone (regardless of age, education, ethnicity, gender, sexual orientation, or any personal characteristics) feels like they belong. Even if your experience doesn’t exactly match up to our job description, you should feel empowered to apply regardless!
