Staff Data Scientist
Mercury · San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States
Posted 14 days ago
or apply directly on Mercury's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 14 days Mercury's roles stay open a median of 42 days
- Reposted
- No
- Salary listed
- No 2% of Mercury's roles list one
- Ghost-job risk at Mercury
- high 26 stale, 1 reposted of 60 open
- Hiring momentum
- 92 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Mercury's own greenhouse board since 2026-08-03. Full hiring picture for Mercury.
About this role
As a Staff Data Scientist at Mercury, you will focus on building, validating, and deploying machine learning models to detect and prevent fraud in real time. You will collaborate with various teams, ensuring data quality and reliability while also documenting and monitoring model performance. This role involves leading technical efforts and driving strategic alignment across teams to enhance fraud defenses and improve customer banking experiences.
- benefits
- 2/5
- freshness
- 4/5
- career value
- 4/5
- role clarity
- 4/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Mercury as an employer.
What you need
- 7+ years of experience working with and analyzing large datasets
- 5+ years of machine learning experience
- Proficiency in SQL
- Proficiency in Python
- Experience deploying and monitoring machine learning models in production
- Comfort working in a fast-paced environment with evolving priorities
Nice to have
- 1+ years of relevant risk experience
- Familiarity with LLMs or other GenAI
- Experience with modern data tools for pipelines and ETL (e.g., dbt)
- Experience with model governance in finance or regulated industries
- Experience building zero-to-one solutions in ambiguous or greenfield problem spaces
What you get
- Base salary
- Equity (stock options/RSUs)
- Highly competitive salary and equity ranges
- Regular updates to compensation based on reliable survey data
Worth weighing
- No specific details on the technology stack used
- Role involves significant leadership and collaboration across teams, which may require strong interpersonal skills
- Fast-paced environment may lead to shifting priorities
Summarised from Mercury's posting. Read the full original.
Listed by Mercury on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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