Greenhouse ·
full-timeSenior Data Scientist - Risk ML
Mercury · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Mercury is a fintech company that provides business banking services through partner banks, offering products such as checking accounts, savings, and cash management tools to startups and growing businesses. The Risk team focuses on detecting and preventing fraud, monitoring customer behavior for financial‑crime risk, and ensuring the safety of the platform. As a Senior Data Scientist on the Risk ML team, you would spend your days designing, training, and validating machine‑learning models that flag suspicious activity in real time, documenting and testing those models to ensure reproducibility, and monitoring data pipelines to maintain quality and reliability. You would work closely with Risk Strategy to define useful features and with Engineering to deploy models into production, adding observability and alerts. The role suits candidates with five or more years of experience handling large datasets, at least three years of applied machine‑learning work, strong SQL and Python skills, and a track record of putting models into production. Familiarity with risk or fraud domains, LLMs, dbt‑based ETL, and model‑governance practices in regulated environments is a plus.
In 1999, NASA lost contact with its Mars Climate Orbiter after a 9-month journey from Earth. It began its planned orbital insertion maneuver but went out of radio contact after passing behind Mars. While we may never know whether it was destroyed in the atmosphere or re-entered heliocentric space, we can draw the lesson that getting the details (in this case, units) right is critical, especially when shooting for the stars. While Mercury’s cosmic journey may be more metaphorical, we have our own sky-high ambitions and the need to marry those with precise data analysis. To that end, we are hiring a Machine Learning-focused Data Scientist to support our Risk team. This team is responsible not only for detecting, monitoring, and mitigating both first- and third-party fraud but also ensuring we know and understand our customers while monitoring their behavior for financial crime risk. You’ll play a key role in strengthening our fraud defenses while ensuring that Mercury continues to deliver a smooth and trustworthy banking* experience. This is an opportunity to join Mercury at a pivotal moment in our growth. You’ll be working on some of the most critical challenges facing the business and collaborating across product, engineering, and risk to protect our customers and the financial system at large. Here are some things you’ll do on the job: 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 optimize deployment and observability You should have: 5+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 3+ 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 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 *Mercury is a fintech company, not an FDIC-insured bank. Banking services provided through Choice Financial Group and Column N.A., Members FDIC. 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. #LI-AC1 Total Rewards The total rewards package at Mercury includes base salary, equity (stock options/RSUs), 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 candidate’s 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 — $250,900 USD Canadian employees (any location): $157,400 — $237,100 CAD
| Role | Senior Data Scientist - Risk ML |
|---|---|
| Company | Mercury |
| Location | San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States |
| Type | internship |
| Compensation | Not disclosed |
| Posted | 2026-09-30 |
| Deadline | Rolling |
Typical process for this type of role
A general guide — the exact steps for this specific listing may vary; check the original posting for details.
- 1ApplicationSubmit your resume through the apply link.
- 2ScreeningRecruiter reviews your background against the role.
- 3AssessmentA technical test, assignment, or coding round, depending on the role.
- 4Interview(s)One or more rounds with the hiring team.
- 5OfferOffer letter with compensation and start date.
Before you apply
0/4Senior Data Scientist - Risk ML at Mercury: frequently asked questions
- What is the salary for this role?
- Mercury has not stated compensation in the listing. Check the original posting or ask during the application process.
- Is the Senior Data Scientist - Risk ML position remote, hybrid or onsite?
- The listing marks this role as remote, with San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States as the location.
- What is the application deadline?
- Mercury has not listed a fixed deadline, so apply early in case the opening is filled.
- How do I apply for the Senior Data Scientist - Risk ML role?
- Use the Apply button on this page. It opens the original listing on job-boards.greenhouse.io, where you submit your application with the company.
More at Mercury
Other jobs at Mercury
- Senior Data Analyst - Reconciliation · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
- Customer Support Manager - Risk · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
- Engineering Manager - Bank Accounts · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
- Senior Analytics Engineer · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
- Senior Engineering Manager - Mobile · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
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