Staff Data Scientist, Tilt

• The ideal candidate is passionate about using data and models to drive business growth and help customers improve their financial situations
• The right person for this role is someone who shines while solving complex problems and is comfortable with a wide variety of technical tools
• BS degree in engineering, computer science, finance or mathematics
• 5+ 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
• At Empower, we hire for people that push themselves to understand others and seek out ways to challenge their personal assumptions

Desirable

• 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
• 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
• 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