Staff Data Scientist - Risk ML
About this role
Mercury is seeking a Staff Data Scientist - Risk ML to join their data team and build advanced machine learning systems. This remote-eligible position, also available in San Francisco, New York, and Portland, is ideal for experienced machine learning professionals eager to tackle complex financial crime and fraud challenges.
Role Overview
In this position, the professional will join a pivotal growth phase at Mercury, focusing on safeguarding the financial system and protecting customers. The role involves designing machine learning solutions that detect and mitigate first- and third-party fraud while maintaining a seamless banking experience. The selected candidate will collaborate closely with engineering, product, and risk strategy teams to scale defenses and drive high-impact technical initiatives.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
Salary and Benefits
Mercury offers a total rewards package that features competitive base salaries, equity opportunities like stock options or RSUs, and comprehensive benefits. The compensation offered depends on factors such as candidate expertise, prior experience, internal equity, and geographic location. For US employees across any location, the target base salary ranges from $239,000 to $298,800 USD. For Canadian employees, the target base salary spans $225,900 to $282,400 CAD.
About the Company
Mercury operates as a fintech company providing financial services through partner banks like Choice Financial Group and Column N.A., Members FDIC. The organization fosters a culture centered on diversity, belonging, and equal employment opportunity, considering all qualified applicants without discrimination.
How to Apply
Interested candidates should visit the official Mercury careers page to submit their application for this opportunity.
Skills and tech stack
Questions candidates ask
What is the primary focus of the Staff Data Scientist - Risk ML role?
The role focuses on building, validating, and deploying machine learning models to detect, monitor, and mitigate first- and third-party fraud while understanding customer behavior for financial crime risk.
What are the experience requirements for this position?
Candidates must have 7+ years of experience working with large datasets to drive impact, including at least 5+ years of dedicated machine learning experience.
Where can the job be performed?
The position is available remotely within Canada or the United States, as well as in office locations including San Francisco, CA, New York, NY, and Portland, OR.
What programming languages and technical tools are required?
Proficiency in Python and SQL is required, along with experience using SQL for imperfect data and Python for statistical modeling and machine learning.
What is the salary range for US-based employees?
The target base salary range for US employees across any location is $239,000 to $298,800 USD, supplemented by equity and benefits.
How should I apply for this position?
Applicants should apply directly through the official Mercury company careers page.