Senior Staff Data Scientist

Role Overview

• Architect and own end-to-end ML systems for personalizing the user experience, including on-demand pay balance optimization
• Design and deploy content personalization systems including email content ranking, in-app experience sequencing, and offer relevance
• Lead the transition from offline batch scoring to real-time, low-latency inference pipelines embedded directly in product backends
• Establish the data infrastructure foundation the data science team requires: feature stores, training pipelines, labeling systems, data contracts, and monitoring frameworks
• Define and enforce data quality standards; design automated validation and alerting pipelines that protect downstream model and business health, implement CI/CD best practices for ML
• Partner directly with product and engineering leads to identify and quantify high-value AI opportunities and translate ambiguous business problems into multi-quarter technical roadmaps
• Communicate complex technical outcomes to executive stakeholders as concrete strategic recommendations, grounded in business impact and financial metrics
• Serve as the primary technical leader for a growing data science team, setting the technical direction, establishing standards, and mentoring data scientists at all levels through design reviews, architectural guidance, and code reviews
• Cultivate a culture of rigor, curiosity, and operational excellence; establish documented, standardized patterns that make the entire team more effective
• Drive cross-functional alignment on DS/AI success metrics, ensuring model performance is durably connected to measurable business outcomes
• Establish team norms and a shared framework for effectively and responsibly applying modern AI; setting expectations around when and how to use AI tools, how to evaluate their outputs, and how to maintain rigor as capabilities evolve rapidly

Requirements

• Advanced degree in a quantitative discipline (e.g., computer science, machine learning, data science, engineering) with 10+ years of industry experience in data science and machine learning
• Demonstrated history of architecting and deploying production ML systems that drive significant, measurable business ROI, preferably across multiple product domains
• Experience in fintech, payments, consumer financial products, or similar regulated domains strongly preferred
• Expert-level proficiency across modern AI, classical ML models, probabilistic methods, optimization techniques, and causal inference; strong track record of translating business objectives into model strategy
• Deep expertise in end-to-end production deployment to engineering standards
• data pipeline development, model observability, monitoring, drift detection, latency/cost tradeoffs, incident response, and rollback planning
• Proven ability to identify where DS/AI creates competitive advantage, prioritize the DS/AI roadmap across product areas, and communicate model performance in terms of business outcomes to senior leadership
• Experience coaching and mentoring senior ICs; ability to shape team technical direction and help build a culture of rigor and inclusion

Benefits

• Exceptional health, vision, and dental care
• Opportunity for equity ownership
• Life and AD&D, short
• and long-term disability
• Employee Assistance Program
• Employee Resource Groups
• Fun company outings and events
• Unlimited PTO
• 401K with company match