Senior Data Scientist (Fintech)

Location: San Francisco, California; New York, New York; Portland, Oregon; or remote within Canada or the United States

Salary: US employees: $166,600–$250,900 USD annually; Canadian employees: $157,400–$237,100 CAD annually

Company

Mercury is a fintech and SaaS company providing banking services through partner financial institutions.

What you will do

• Build, validate, and deploy machine learning models for real-time fraud detection and prevention.
• Document, test, and monitor models to support reproducibility and robustness.
• Ensure data quality and reliability across data pipelines and tools.
• Collaborate with Risk Strategy to develop model inputs and applications.
• Work with Engineering to optimize model deployment and observability.

Requirements

• 5+ years of experience analyzing large datasets to solve problems and drive impact, including 3+ years of machine learning experience.
• Proficiency in SQL and experience managing imperfect data.
• Proficiency in Python, statistical modeling, and machine learning.
• Experience deploying and monitoring machine learning models in production.
• Ability to work effectively in a fast-paced environment with evolving priorities.
• Must be located in the United States or Canada for remote work.

Nice to have

• At least 1 year of relevant risk experience.
• Familiarity with LLMs or other generative AI applications in risk or fraud detection.
• Experience with modern data pipeline and ETL tools such as dbt.
• Experience with model governance in finance or other regulated industries.
• Experience building zero-to-one solutions in ambiguous or greenfield problem spaces.

Culture & Benefits

• Total rewards include base salary, equity through stock options or RSUs, and benefits.
• Compensation is adjusted based on experience, expertise, geographic location, and internal pay equity.
• Mercury is committed to diversity, belonging, equal employment opportunity, and reasonable accommodations throughout the recruitment process.