Data Analyst

Reports to: Senior Manager, Revenue Analytics

Location: Remote (US-based)

About Cherry
Cherry is a fast-growing fintech company revolutionizing how patients pay for care. Founded in 2019 by Stanford entrepreneurs (with a prior successful exit), Cherry has built the simplest, fastest, and most inclusive Buy Now, Pay Later solution for healthcare services—from dental and medical aesthetics to veterinary care.

By making treatments more financially accessible, Cherry empowers medical practices to serve more patients. We’re backed by leading investors including Kleiner Perkins and DCM, and we're just getting started.

About the Role
We are hiring a Senior Data Analyst to own Sales Analytics across Cherry. You will sit at the center of our go to market engine and turn raw data into the insights that shape strategy, headcount, territories, compensation, and how we deploy our sales team every day.

You will work across Snowflake, dbt, Metabase, Tableau, and Hex to connect the dots between top of funnel activity, pipeline quality, forecast accuracy, and actual revenue. Your work will shape how we set targets, how we deploy our teams, how we understand risk, and how we measure the health of every practice in our portfolio.

This is a hands-on role for someone who cares about impact. You will go deep on raw data, build models, own core metrics, and work directly with senior operators who rely on your insights to steer the business.

Responsibilities

• Strategic and Predictive Initiatives

  • Design and maintain predictive models that help the company anticipate revenue outcomes, retention patterns, and practice behavior.

  • Create frameworks that score or segment accounts based on potential, risk, or lifecycle signals.

  • Develop analytical tools that improve how we allocate resources, prioritize accounts, or identify emerging trends.

  • Incorporate new data sources or enrichment methods to strengthen our understanding of the market and our customer base.

  • Lead cross functional efforts to translate analytical findings into changes in process, priorities, or go to market strategy.

  • Drive long horizon analytics work that raises the accuracy, reliability, and scale of our decision making over time.

• Performance and Growth Analytics

  • Own core revenue KPIs, operating results, and weekly performance reporting.

  • Build and maintain dashboards for quota, attainment, pipeline health, retention, and other key metrics.

  • Calculate incentive compensation for revenue teams on a monthly and quarterly basis.

  • Support quarterly planning with quota, capacity, coverage, and segmentation inputs.

  • Conduct deep dives on pipeline, forecast accuracy, conversion rates, churn drivers, and competitive performance.

  • Run segment and industry analysis to surface growth opportunities or performance gaps.

  • Perform root cause analysis when key metrics shift unexpectedly.

  • Provide clear, concise insights for leadership reviews, quarterly planning, and forecast discussions.

• Data Modeling and Infrastructure

  • Build and maintain clean, reliable data models in dbt.

  • Develop metric definitions, documentation, and logic that keep reporting consistent.

  • Improve data quality by identifying inconsistencies, missing fields, or model issues.

  • Automate repetitive reporting through scalable pipelines and models.

  • Maintain the integrity of our data across our platforms.

• Storytelling and Influence

  • Translate complex data into simple, compelling narratives for senior leaders.

  • Communicate technical findings and concepts to non-technical audiences.

  • Build visuals and written insights that drive clarity and decision-making.

  • Elevate the analytics function by setting a high bar for communication, documentation, and analytical rigor.

Qualifications

• 2-3+ years of experience in analytics, preferably supporting Sales, RevOps, CS, or lifecycle analytics.

• Bachelor’s degree in a STEM field with strong academic performance.

• Strong SQL skills and experience working in a warehouse environment.

• Experience with Tableau, Metabase, or similar BI tools.

• experience using AI tools like Claude or Cursor in your analytics work

• Ability to independently translate loose questions into structured analysis.

• Strong communication skills with a focus on clarity and directness.

• Ability to balance recurring operational work with long-term analytical initiatives.

• Comfortable operating in a fast-paced, high-growth environment.

• Exposure to Python / Python experience preferred