Senior Staff Data Scientist

DailyPay

Senior Staff Data Scientist architecting and owning ML systems for personalization in the fintech space. Leading technical direction and mentoring a growing data science team for DailyPay.

Posted 5/15/2026full-timeNew York City • New York • 🇺🇸 United StatesSenior💰 $215,000 - $294,000 per yearWebsite

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdata sciencereal-time inference pipelinesfeature storestraining pipelinesautomated validationCI/CD best practicesprobabilistic methodsoptimization techniquescausal inference

Soft Skills

leadershipcommunicationmentoringcross-functional alignmentstrategic thinkingoperational excellencecuriosityteam buildingtechnical directionstandardization

Certifications

advanced degree in quantitative discipline