Data Scientist, Unison Home Ownership Investors

• This is a high-impact role for someone who thrives on ownership, intellectual curiosity, and delivering work they are proud to present
• Master’s degree in Quantitative Finance, Financial Engineering, Data Science, Statistics, Operations Research, or a related quantitative discipline
• Two or more years of experience in data science, quantitative finance, data engineering, or software engineering
• Strong programming skills in Python and proficiency in SQL
• Experience with or willingness to learn distributed data tools such as Hadoop and Spark, as well as AWS cloud services
• Demonstrated experience developing and deploying machine learning models
• Passion for integrating AI-driven solutions into business workflows
• We recognize that people come with experience and talent beyond just the technical requirements of a job. If your experience is close to what you see listed here, please still consider applying. Diversity of experience and skills combined with passion is a key to innovation and excellence. Therefore, we encourage people from all backgrounds to apply to our positions

Desirable

• Unison is seeking a Data Scientist to power the next generation of our home equity sharing platform. This role sits at the intersection of product, engineering, and investments, driving the analytical insights and machine learning capabilities that enable us to scale efficiently and profitably
• You will translate complex data into actionable intelligence, build and deploy predictive models, and partner cross-functionally to shape product strategy and portfolio performance
• Develop a deep understanding of Unison’s equity sharing products and customer journey
• Define, track, and forecast key product and funnel metrics across acquisition, conversion, and retention
• Partner closely with Product, Marketing, and Engineering to translate business questions into scalable data science solutions
• Deliver clear, actionable insights that inform product decisions and growth strategy
• Design, train, validate, and maintain machine learning models using data such as property attributes, customer characteristics, macroeconomic indicators, and conversion data
• Enhance model performance through feature engineering, model selection, hyperparameter tuning, and ongoing monitoring
• Productionize models to ensure scalability, reliability, and performance in live environments
• Establish best practices for model governance, documentation, and lifecycle management
• Build cash flow models that incorporate home price dynamics, turnover assumptions, and product terms
• Forecast prepayment behavior, default rates, home price appreciation, and portfolio returns
• Identify data-driven insights that improve the portfolio’s risk-return profile
• Support strategic initiatives through rigorous quantitative analysis
• Build and maintain scalable applications and workflows on AWS
• Design and support data pipelines and infrastructure to enable analytics and machine learning at scale
• Write clean, efficient, and well-documented code aligned with best practices