In the 1970s, engineer Edgar Codd proposed a radical idea: instead of the hierarchical databases his employer IBM used and sold, he proposed the concept of “relational databases” to manage large datasets. His ideas, codified with a set of rules called Codd's 12 rules, fundamentally transformed how we store, retrieve, manipulate, and manage data, enabling advancements across various sectors of society and industry.
We’re looking for a Director of Data who can help us use the approaches that led to the creation of relational databases to drive Mercury’s success.
In this role, you’ll lead a full-stack data organization of 30+ data scientists and data engineers embedded across Mercury’s business and product teams. You’ll define how data is built, governed, and leveraged — shaping a culture where anyone can access trusted data, ask hard questions, and self-serve at scale. You’ll architect the systems that help Mercury move faster, invest smarter, and make better decisions at every level.
Here are some things you’ll do on the job:
- Build, lead, and develop a high-performing team of 30+ data scientists and data engineers embedded across GTM, Core Product, and Risk, ensuring Mercury’s most important decisions are grounded in rigorous, trusted data.
- Define and execute a forward-looking data strategy that embeds rigorous, data-driven decision-making into how Mercury sets company priorities, builds products, and manages risk.
- Lead Mercury’s evolution toward self-serve data at scale by shipping high-leverage data platforms that empower teams to move quickly from question to insight to action.
- Elevate data reliability, governance, and security as core capabilities by shaping the standards and systems required to operate as a scaled financial institution.
You should:
- Have 10+ years of experience, including 4+ years managing a team of data science or data engineering managers.
- Track record of partnering with and influencing executives, equipping them with the tools, reporting, and advanced analytics needed to make decisions — proactively surfacing opportunities and risks they may not see.
- Bring strong opinions on how data should inform decision-making, with the ability to translate that perspective into scalable practices and standards.
- Have deep expertise in data science, machine learning, statistics, financial calculations, and experimentation for commercial applications.
- Experience developing high-performing data teams, setting a high talent bar while fostering an inspiring environment of ownership, growth, and impact.
- Have developed self-service analytics capabilities at scale, expanding access to relia