Senior Data Scientist - Fraud (San Francisco) Job at Mercury, San Francisco, CA

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  • Mercury
  • San Francisco, CA

Job Description

Get AI-powered advice on this job and more exclusive features. Mercury is building the financial stack for startups. Were here to make banking* intuitive, powerful, and safe for entrepreneurs and businesses of all sizes. We started by imagining what the best banking platform for startups would look like, and several years later we have hundreds of thousands of customers using Mercurys products. As we continue to scale, protecting our customers and Mercury from fraud while still ensuring the seamless customer experience we have come to be known for is critical.

We are hiring a Data Scientist to join our Fraud and Limits team. This team is responsible for detecting, monitoring, and mitigating both firstparty fraud (fraudulent applicants) and account takeover (ATO). Youll play a key role in strengthening our fraud defenses while ensuring that Mercury continues to deliver a smooth and trustworthy banking experience.

Responsibilities

  • Develop dashboards and monitoring systems to track key fraud and account health metrics.
  • Conduct deepDive analyses to understand fraud trends and behaviors, and translate findings into actionable recommendations.
  • Build, validate, and deploy machine learning models to identify and prevent fraud in real time.
  • Support ad hoc investigations and ensure data quality and reliability across pipelines and tools.
  • Collaborate with Risk Strategy and Engineering to optimize rules, scoring systems, and other fraud defenses.
  • Partner with crossfunctional teams (Engineering, Product, Design, Operations) to embed data insights into decisionmaking.

Qualifications

  • 5+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 1+ years of relevant domain 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.
  • The ability to balance highleverage projects with foundational work such as reporting, dashboarding, and exploratory analyses.
  • Comfort working in a fastpaced environment with evolving priorities.

Desired (Optional)

  • Experience building zerotoone solutions in ambiguous or greenfield problem spaces.
  • 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).

Compensation and Benefits

The total rewards package at Mercury includes base salary, equity (stock options), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidates experience, expertise, geographic location, and internal pay equity relative to peers.

US employees (any location): $166,600 - $208,300 USD

Canadian employees (any location): CAD 157,400 - 196,800

Equal Employment Opportunity

Mercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic. We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

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Job Tags

Full time,

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