Data Science Manager - Risk

In 1969, Katherine Johnson was tasked with calculating the flight trajectories of the Apollo 11 mission to the moon. Her years of experience helped shape a backup plan featuring a one-star observation system that would allow astronauts to determine their location with accuracy. This plan became critical when the mission was aborted and charts helped set a safe path for the crew's return to Earth.  

We’re looking for a leader of the Risk Data Science team to leverage their experience to build, grow and manage a team of skilled Data Scientists that enable Mercury to scale powered by the fraud controls this team helps build.

In this role, you’ll be responsible for a team of 3-5 data scientists embedded in our Risk teams, and will critically influence how we invest in and build Mercury’s future. You’ll be early in building a data-informed culture across Mercury so that stakeholders across the company can determine what's happening, react quickly, and invest intelligently.

Here are some things you’ll do on the job:

• Build, manage, and develop a team of 3-5 data scientists to help Mercury make better business banking* and product decisions informed by data.
• Influence analytics culture and rigor across our Risk Products (infra, experience, intelligence, etc) by working with different levels, from executives to individual product and operations teams, ranging from deriving insights of our risk operations flows to advanced statistical methods for risk and credit underwriting.

You should:

• Have 5+ years of experience in a quantitative role managing risk for financial products, including 2+ years managing a team of quantitative experts (e.g. data scientists, product analysts, machine learning engineers, or financial mathematicians).
• Be able to partner with business leaders and GMs to ensure that they and their teams have the tools, reporting and support to consistently make the best data-informed decisions. Proactively provide advanced analytics and insights to leaders that stakeholders may not be seeing.
• Be opinionated on the ways to most effectively use data to make business and product decisions.
• Strong knowledge and hands-on experience with data science, machine learning, statistics, financial calculations, or experimentation for commercial applications.

Our salary ranges are based on paying competitively for our size and industry, and all employees receive salary + equity + benefits. Individual pay decisions are based on a number of factors, including qualifications for the role, experience level, skillset, and balancing internal equity relative to peers at the company.

The range shared is for the expectations as laid out in the job description, however we are often open to a wide variety of profiles, and recognize that the person we hire may be less experienced or more senior than this job description as posted. If that ends up being the case, the updated salary range will be communicated with you as a candidate.

The salary range for candidates in the US is $237,600–$279,500.

The salary range for candidates in Canada is CAD 216,200-254,300.

*Mercury is a financial technology company, not a bank. Banking services provided by Choice Financial Group and Evolve Bank & Trust ®️; Members FDIC

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