Data Analyst — Product Analytics

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Analyst — Product Analytics based in United States. This is a high-ownership analytics role focused on making client billing data accurate, reliable, and actionable. You’ll work at the intersection of Product Analytics, Client Operations, Finance, and Engineering to solve complex data challenges. Your initial focus will be reconciling cross-system billing data, investigating discrepancies, and establishing durable data-quality controls. As the role evolves, you’ll help reduce billing friction through improved processes, stronger data flows, and automation. You’ll turn messy datasets into trustworthy reporting that helps teams identify trends, risks, and anomalies before they affect clients. The environment is collaborative, agile, and fast-moving, with significant autonomy and opportunities to improve how data supports the business. This role is ideal for an analytical problem-solver who takes pride in precision and enjoys simplifying complex data landscapes. Accountabilities

• Reconcile and validate client billing data across multiple internal systems, investigating discrepancies and driving them through to resolution.
• Build repeatable data-quality checks, reconciliation processes, documentation, and controls that improve billing accuracy and reliability.
• Partner directly with Client Operations to support timely and accurate billing and answer high-priority data questions.
• Develop and maintain reporting, dashboards, and analyses that highlight billing trends, risks, anomalies, and opportunities for improvement.
• Identify and implement process improvements that reduce client billing friction, strengthen data flows, and increase operational efficiency.
• Explore opportunities to automate recurring reconciliation, reporting, and data-quality workflows.
• Collaborate with Product Analytics, Finance, Engineering, and other stakeholders to understand source systems and improve the data infrastructure supporting billing.
• Work effectively in an agile environment, balancing multiple priorities and adapting quickly as business needs evolve.
• Maintain a high standard of data integrity when working with complex and imperfect datasets, including sensitive information subject to healthcare privacy requirements.

Requirements

• Experience: At least 2 years of experience in analytics, data, finance operations, or a closely related role. (The source description appears to contain a typo stating “52+ years”; this has been interpreted as 2+ years.)
• Advanced Excel skills, including pivot tables, lookups, large-dataset manipulation, and data reconciliation.
• Strong SQL skills and confidence working with relational databases.
• Demonstrated experience reconciling data across multiple systems and investigating and resolving discrepancies.
• Exceptional attention to detail and a consistently high standard for data accuracy and integrity.
• Ability to work effectively with imperfect or incomplete data while maintaining sound analytical judgment.
• Strong prioritization skills and adaptability in a dynamic environment where requirements and priorities can shift.
• Clear written and verbal communication skills, with the ability to collaborate effectively with both technical and non-technical stakeholders.
• Strong ownership mindset, initiative, curiosity, and a willingness to identify problems and improve processes proactively.
• Nice to have: Experience working with healthcare data, including medical or pharmacy claims or accounts receivable.
• Nice to have: Familiarity with billing, revenue operations, or accounts-receivable processes.
• Nice to have: Experience creating dashboards or reporting in BI platforms such as Looker or Tableau.
• Nice to have: Exposure to BigQuery, dbt, or comparable data-warehouse technologies.
• Nice to have: Python or scripting experience.
• Nice to have: Knowledge of data governance, data-quality frameworks, or internal controls.

Benefits

• Competitive salary range of $96,000–$124,500, depending on qualifications, experience, and location.
• Equity opportunities.
• Fully remote, remote-first work environment.
• Office hubs available in Denver and San Francisco.
• Opportunities to work on meaningful healthcare and data challenges with cross-functional teams.
• A collaborative, transparent, evidence-based culture that values ownership, initiative, and positive impact.
• Opportunities to improve processes and introduce automation in a growing Product Analytics organization.
• Training and procedures to support the secure handling of sensitive, HIPAA-protected information.
• Comprehensive employee benefits, with offerings available through the company's careers and benefits program.
• A culture that emphasizes employee well-being, trust, empowerment, continuous learning, experimentation, and rapid iteration.
• Location-based compensation: Eligibility and compensation may vary based on the employee's location; certain states may be excluded from hiring eligibility.

How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.