• Develop and implement advanced statistical and machine learning models to predict loan performance, borrower risk, prepayment likelihood, and renewal opportunities • Partner with credit, portfolio management, and lending teams to identify high-impact use cases for data-driven solutions • Automate data ingestion, transformation, and reporting processes to streamline analytics workflows • Build dashboards and data visualizations that communicate insights effectively to executive and front-line stakeholders • Design and execute experiments and A/B tests to measure the effectiveness of lending strategies and risk policies • Leverage R or Python for model development, statistical analysis, and data manipulation • Work with structured and unstructured data, including loan files, collateral valuations, market data, and financial statements • Stay informed on emerging AI techniques and assess their applicability to commercial lending and banking operations • Mentor analysts and contribute to building a data-driven culture within the Bank • Perform other duties as assigned

• Own end-to-end product experimentation: hypothesis generation, metric definition, experimental design (A/B, multivariate, sequential testing), analysis, and executive-level interpretation. • Design and maintain ML-powered evaluation frameworks for product changes, automation quality, and system reliability (e.g., order accuracy, routing, error rates, conversion). • Build and deploy predictive models, classifiers, and ranking systems that power experimentation, personalization, and product optimization. • Partner with product and engineering to test new features, workflows, and ML models through controlled experiments and incremental rollouts. • Lead offline and online model evaluation, comparing baselines, candidate models, and product variants using rigorous statistical methods. • Use causal inference and quasi-experimental methods when randomized experiments are not feasible. • Develop experiment pipelines and instrumentation: logging, dashboards, monitoring, and automated analysis to ensure measurement integrity. • Perform failure-mode and error analysis to guide product iteration and model improvement. • Translate experiment outcomes into clear product decisions, influencing roadmap prioritization and system design. • Drive experimentation at scale in a fast-moving environment, balancing speed, rigor, and business impact. • Lead and mentor data scientists and analysts, setting standards for experimentation, modeling, and evaluation across the organization.

• Design, evaluate, and interpret experiments in the presence of network effects, delayed outcomes, and imperfect randomization—balancing speed with statistical rigor. • Influence product direction by translating insights into clear recommendations that shape roadmap prioritization. • Develop key strategic insights through exploratory data analysis, to inform future investments or pivot in strategy • Build scalable metrics and dashboards to empower efficient decision-making • Own the definition and evolution of success metrics for core engagement surfaces, including tradeoffs between short-term and long-term member value.

• Leverage your technical and business acumen to become a specialist in our models, products, business and how the models interact with the business. • Identify potential problems or opportunities for improvement, communicate these issues to the team and suggest solutions. • Involves self-directed investigation into Upstart’s data and product, offline analyses using creative thinking as well as presentation to the ML team. • Receive mentorship from experienced DS/ML practitioners and collaborate closely with ML scientists to improve our products and models via data-driven insights. • Understand the underpinnings of ML models and how they create value for the business. • Identify data sources, use statistical methods and write clean code to conduct offline analyses about ML models and/or Upstart products. • Communicate findings clearly to get buy-in for recommended next steps. • Work with your mentor to align stakeholders, and drive next steps.