Senior Data Scientist - Fraud

San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States Overview Mercury is building the financial stack for startups. We’re 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 Mercury’s products. As we scale, protecting our customers and Mercury from fraud while maintaining a seamless customer experience 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 first-party fraud (fraudulent applicants) and account takeover (ATO). You’ll play a key role in strengthening our fraud defenses while ensuring Mercury delivers a smooth and trustworthy banking experience. This is an opportunity to join Mercury at a pivotal moment in our growth. You’ll work on critical challenges and collaborate across product, engineering, and risk to protect our customers and the financial system at large. Responsibilities Develop dashboards and monitoring systems to track key fraud and account health metrics. Conduct deep-dive 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 cross-functional teams (Engineering, Product, Design, Operations) to embed data insights into decision-making. 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 high-leverage projects with foundational work such as reporting, dashboarding, and exploratory analyses. Comfort working in a fast-paced environment with evolving priorities. Nice-to-have Experience building zero-to-one 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 competitive within the SaaS and fintech industry and updated using compensation survey data. New hire offers are based on experience, expertise, geographic location, and internal pay equity relative to peers. Our target new hire base salary ranges for this role are the following: US employees (any location): $166,600 - 208,300 USD Canadian employees (any location): CAD 157,400 - 196,800 Note: Mercury is a financial technology company, not a bank. Banking services provided through Choice Financial Group, Column N.A., and Evolve Bank & Trust, Members FDIC. Equal 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 provide reasonable accommodations throughout the recruitment process for applicants with disabilities or special needs. If you need assistance, please let your recruiter know after you are contacted about a role. We use Covey as part of our hiring process for jobs in NYC and certain features may qualify it as AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submissions. See the independent bias audit report covering our use of Covey here. #LI-RA1 #J-18808-Ljbffr

Created: 2025-10-03