Staff Data Scientist

Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC.

• Build, validate, and deploy machine learning models to identify and prevent fraud in real time.
• Support the reproducibility and robustness of said models through documentation, testing, and monitoring.
• Ensure data quality and reliability across pipelines and tools.
• Collaborate with Risk Strategy to ideate on model inputs and applications and with Engineering to optimize deployment and observability.
• Act as a technical lead prototyping, iterating on, and codifying best practices - and bringing the rest of the team along.

• 7+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 5+ years of ML experience.
• Proficiency in SQL and experience using it to understand and manage imperfect data.
• Proficiency in Python and experience with statistical modeling and machine learning.
• Experience deploying and monitoring machine learning models in production.
• Comfort working in a fast-paced environment with evolving priorities.
• Demonstrated ability to lead and empower others, delivering not just on your own work, but upleveling those around you.
• The ability to drive strategic alignment between teams with differing roadmaps, timelines, or architectures.
• Ideally you also have: 1+ years of relevant risk experience; familiarity with LLMs or other GenAI and how they can be applied to risk or fraud detection; experience with modern data tools for pipelines and ETL (e.g., dbt); experience with model governance as required in finance or other regulated industries; experience building zero-to-one solutions in ambiguous or greenfield problem spaces.

• Total rewards package includes base salary, equity (stock options/RSUs), and benefits.
• Target new hire base salary ranges: US employees (any location): $239,000 — $298,800 USD; Canadian employees (any location): $225,900 — $282,400 CAD.