Data Scientist (Growth)

About the role

The Data Scientist at Rox will power the intelligence layer behind the world’s first revenue operating system. You will be responsible for metrics, insights, and analytical frameworks that shape product development, business operations, and customer transformation.

Responsibilities

• Build and maintain dashboards, KPIs, and the company-wide single source of truth for revenue, usage, and customer telemetry.
• Partner with GTM leaders to drive segmentation, funnel insights, measurement of workflow adoption and ROI.
• Build and maintain COGS and unit-economics models with Finance, providing the business with a clear view of cost-per-action and margin by customer and product.
• Own and improve dbt/Paradime models and Snowflake pipelines, ensuring data quality, reliability, and consistency.
• Ship self-serve tooling (internal data apps, dbt models, and Sigma dashboards) that GTM and Finance rely on without hand-holding.
• Deliver deep product and usage analytics, including cohort and uplift analysis, to measure adoption, support enterprise rollouts, and inform product decisions.
• Deliver clear, defensible analyses to support leadership and new revenue motions, framing the metric, the method, and the "so what."
• Create scalable documentation, metric dictionaries, automations, and enablement materials while onboarding teams into Rox’s data ecosystem.

Qualifications

• Required: Degree in a quantitative field (e.g., Mathematics, Economics, Computer Science, Engineering, Statistics); 2–5+ years experience in fast-paced, high-growth companies supporting Sales, Finance, or Product; Strong SQL and Python skills; Experience working with dbt ecosystems; Exceptional analytical rigor and structured problem-solving skills; Strong communication skills; High energy, “no job is too small” mentality; Ability to context-switch rapidly and thrive in an environment of speed, ambiguity, and high expectations; Located in or willing to relocate to San Francisco.
• PREFERRED: Experience at a consumption or usage-based business (e.g., Datadog, New Relic, Snowflake), with fluency in usage metering and unit economics; Finance / FP&A background with experience building and owning COGS, margin, or cost models; Experience working directly with GTM organizations and leadership teams; Knowledge of revenue methodologies, KPIs, and operational models; Familiarity with data warehousing technologies; Experience designing semantic layers and metric governance processes; Experience building minimal data apps, Python scripts, or automations to scale workflows; Experience supporting enterprise customers or working with B2B SaaS telemetry datasets; Strong intuition for business levers, product adoption mechanics, and cohort analysis; Comfort with AI-native development tools such as Cursor and Claude Code to move quickly.

Benefits

Competitive pay with considerable equity upside
Health Insurance

Apply

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