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DailyPay is the leader in On-Demand Pay, serving over 1,900 employers and 6 million employees. The company modernizes how people access their earned pay and provides financial wellness tools.
You will join the Data Science team as a Senior AI & ML Scientist in a high-impact individual contributor role. You will build and maintain machine learning models and decision systems that personalize the DailyPay product experience, including optimizing financial decisions for workers, personalizing communications and user experiences, and supporting fraud controls.
Key responsibilities:
- Build, improve, and maintain ML models for personalizing user experience, including on-demand pay balance optimization, content personalization, and fraud controls
- Develop reliable data pipelines and features for model development, following team infrastructure standards
- Develop, evaluate, deploy, monitor, and improve both batch and real-time models following production standards
- Stay current on AI/ML developments and apply sound judgment in algorithm selection and technique adoption
- Write clean, well-documented, traceable, versioned, and reproducible code following team standards
- Follow and contribute to data quality standards and validation practices
- Partner with product and engineering teams on scoped problem areas, translating business questions into data science solutions
- Communicate model results and tradeoffs clearly to product and cross-functional partners, connecting technical outputs to business outcomes
This role is ideal for someone who executes complex modeling work with excellence and is ready to grow their strategic influence across product and business stakeholders.
Requirements:
- 5+ years of Machine Learning experience within fintech, payments, or similarly regulated consumer domain
- Proven track record of shipping production models that directly impact end-user experience
- Bachelor's or advanced degree in a quantitative discipline (computer science, machine learning, statistics, data science, or related field)
- Track record of independently building models that drive measurable business outcomes, with experience seeing work through to production
- Experience building and maintaining reliable feature engineering pipelines with advanced SQL and Python skills
- Working knowledge of data infrastructure that supports model development at scale
- Hands-on experience with end-to-end model deployment, including data pipelines, model monitoring, drift detection, and A/B test execution
- Strong instinct for production reliability
- Experience owning models in production environments where failures have real financial or compliance consequences
- Strong proficiency across modern AI, classical ML, statistical, and probabilistic methods
- Ability to translate well-defined business objectives into modeling approaches and evaluate them rigorously
