Data Analyst

About Us

Rho is the modern banking platform built for the AI era. Startups and growth-stage companies can open accounts in minutes, issue cards, manage expenses, pay bills, and close the books – all in one connected platform backed by real human support.

About the Role

Rho’s data has two types of consumers: people and AI agents. As our data analyst, you will empower both with reliable data and meaningful insights. This is a hands-on, end-to-end role that involves everything from data pipelining to delivering recommendations. You will model new data for Rho’s latest features and product lines. You will build the semantic layer that defines how Rho measures itself and turn analyses into decisions with stakeholders across the whole business.

The increased adoption of agentic tools and the acceleration of Rho’s own product velocity result in more people consuming data, more data-backed outputs, and even more business questions to answer. More than ever, it’s imperative that a data team ensures reliable self-service data for routine reporting or inbound requests while being hands-on for deeper analysis that drives decision-making.

You’re accountable for faster and data-driven decision-making, not for the number of dashboards or reports built. This is a cross-functional role that will interface with data engineering as well as business-side stakeholders from GTM, Product, and other departments. This role is based in our New York office and reports to our Manager, Product Analytics who is also based there.

Pay

- Our target compensation range for this role is: $120K to $150K, with variation based on relevant experience, skills, and business needs. In addition to base pay, Rho offers equity, comprehensive healthcare benefits, and paid time off.

Responsibilities

Drive business decision-making by working directly with stakeholders across the company to scope ambiguous questions, conduct analyses, and transform analyses into clear, actionable recommendations.; Proactively uncover opportunity areas as a holder of domain knowledge across verticals. Operate flexibly across verticals and function as a subject matter expert on data sources and key metrics.; Empower Rho’s internal data consumers. Enhance data enablement through building and maintaining models via dbt. Own the end-to-end process: onboard raw warehouse data, add relevant tests and documentation, curate end-user tables, and debug any subsequent breakages.; Ensure that data is accurate and useful for end-users, analysts, and AI agents by collaborating with data engineering and sharing relevant business context.; Uphold data integrity and governance standards by maintaining consistent metric definitions within the dbt semantic layer.; Own BI reporting for multiple verticals, ranging from Compliance to GTM. Build or tune any required reporting, and safely deprecate obsolete assets.

Requirements

2 to 4 years of experience as a data analyst, business analyst, analytics engineer, business intelligence engineer, or similar role; A growth mindset and ability to quickly learn about new business domains or product surface areas in a fast-moving environment; Outstanding SQL ability, and particularly comfortable with debugging complex logic; Track record of translating data insights into actionable recommendations for stakeholders; Hands-on experience building models in dbt or similar data transformation frameworks; Excellent written and verbal communication, with the ability to adapt to audiences of varying technical backgrounds; You already use AI to move faster, whether it’s by automating repetitive tasks or drafting initial analyses. You are curious about what’s next.; Prior experience in building or maintaining dashboards in Looker, Omni, Hex, Tableau, and other business intelligence or analytical tools

Nice to have

Experience working in financial services, banking, technology or a fast-paced startup; Experience supporting multiple verticals or departments simultaneously; Experience building out a dbt semantic layer and refining the warehouse as a surface area for both humans and AI agents; Familiarity with machine learning concepts and predictive analytics