Staff Data Scientist

Posted 2 Days Ago
Hiring Remotely in San Francisco, CA, USA
In-Office or Remote
239K-299K Annually
Senior level
Fintech
The Role
Build, validate, deploy, and monitor machine learning models for real-time fraud detection and financial crime risk. Ensure data quality, model reproducibility, and production reliability while collaborating with Risk Strategy, Product, and Engineering. Lead prototyping, establish best practices, and align teams across differing roadmaps. The role also supports model governance, modern data pipelines, and potential applications of LLMs and generative AI in risk and fraud detection.
Summary Generated by Built In

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
  • Act as a technical lead prototyping, iterating on, and codifying best practices - and bringing the rest of the team along
You should have:
  • 7+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 5+ 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
  • Demonstrated ability to lead and empower others, delivering not just on your own work, but upleveling those around you
  • The ability to drive strategic alignment between teams with differing roadmaps, timelines, or architectures
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):
$239,000$298,800 USD
Canadian employees (any location):
$225,900$282,400 CAD

Skills Required

  • 7+ years of experience working with and analyzing large datasets to solve problems and drive impact
  • 5+ 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 in a fast-paced environment with evolving priorities
  • Demonstrated ability to lead and empower others
  • Ability to drive strategic alignment between teams with differing roadmaps, timelines, or architectures
  • 1+ years of relevant risk experience
  • Familiarity with LLMs or other generative AI and their applications to 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
Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: San Francisco, CA
150 Employees
Year Founded: 2017

What We Do

Mercury is building banking for startups. We want to power the next generation of companies that will shape American industry.

Similar Jobs

Nextdoor Logo Nextdoor

Data Scientist

Information Technology • Other • Social Media
Remote
US
780 Employees
190K-283K Annually

Stack Overflow Logo Stack Overflow

Data Scientist

AdTech • Artificial Intelligence • Cloud • Edtech • Enterprise Web • Productivity • Software
Remote
US
514 Employees

Gradient AI Logo Gradient AI

Data Scientist

Artificial Intelligence • Insurance • Machine Learning • Software • Analytics
Easy Apply
Remote or Hybrid
USA
130 Employees
160K-194K Annually

SmithRx Logo SmithRx

Data Scientist

Pharmaceutical
Remote
USA
46 Employees
194K-228K Annually

Similar Companies Hiring

Hanover Park Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
42 Employees
Kepler  Thumbnail
Artificial Intelligence • Fintech • Software
New York, New York
9 Employees
Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account