Data Analyst, Operations

Remote: yes Posted: 2026-10-22

ABOUT ROCKET MONEY 🔮

Rocket Money’s mission is to empower people to live their best financial lives. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey.

The Rocket Money Data Analytics team is comprised of data analysts who are passionate about using data to drive business decisions and improve user experiences. Analysts work within a semi-embedded organizational structure to independently build data analytics tooling, drive strategy with data, and assess experiments within cross-functional product vertical aligned teams. Analysts also work closely with other members of the analytics engineering and data science teams to further our product delivery, operations, finance, and marketing goals.

We’re growing the team and hiring a Data Analyst to deepen our partnership with Operations and Customer Support teams. In this role you’ll bring a strong analytic point of view to concrete operational problems — shaping measurement and reporting, leading ad hoc investigations, and delivering actionable insights—while helping raise the bar for how we use data to improve member outcomes.

Tech Stack: BigQuery, dbt, Looker, Amplitude, Deepnote

- Partner semi-embedded with operations and customer support management teams to own complex analytic work end-to-end: framing questions, defining measurement, and delivering narratives that influence roadmap decisions with a clear point of view grounded in evidence.

- Build trusted relationships with operations leadership and relevant cross-functional partners, communicating tradeoffs managing expectations through ambiguity, and ensuring analytics engagement lands at the right moments.

- Lead high-impact ad hoc analyses that surface non-obvious opportunities or trends in operations data; proactively follow insights through to recommendations which will directly impact customer outcomes.

- Be a force multiplier for the team via creating self-service analytics: contributing dashboards, metric definitions, reusable queries/notebooks, and documentation so recurring questions scale.

- Proactively seek out creative ways to apply data analytics methods and tools within the operations space. Guide and educate stakeholders and partners in the usage of these tools to support their decision-making process.