Senior Business Analytics Associate

We are looking for a Senior Business Analytics Associate to help build the data foundation and intelligence layer that enables Abby Care to scale care delivery, improve clinical outcomes, and power an AI-native operating system for home care.

Reporting to the Head of Data Analytics, you will independently lead high-impact analytics initiatives across Operations, Clinical, Finance, Product, and Engineering. You will turn ambiguous business problems into trusted metrics, rigorous analyses, and recommendations that shape company decisions.

This is a full-time, hybrid role based in San Francisco, California.

• Own analytics for one or more critical business domains and serve as a trusted partner to functional leaders.

• Define company metrics, reusable data models, and dashboards that create a shared source of truth.

• Identify the drivers of funnel conversion, time to start of care, prior authorization outcomes, caregiver engagement, operational efficiency, and revenue performance.

• Develop forecasting, prioritization, and risk-detection models for operational and financial decisions.

• Define and operationalize clinical quality and outcomes measurement.

• Partner with Engineering and Product on canonical data models, lifecycle events, and the metrics layer powering AbbyOS and AI-enabled workflows.

• Establish measurement frameworks for product adoption, operational changes, and experiments.

• Improve the quality, scalability, and reproducibility of analytics through automation, documentation, and modern data practices.

• Translate complex analyses into clear executive-level recommendations and actions.

• 4+ years of experience in business analytics, data analytics, business intelligence, product analytics, data science, or a related field.

• Advanced SQL skills and strong proficiency in Python or R.

• Demonstrated ability to independently define and lead complex analytical projects.

• Experience translating ambiguous business questions into analytical frameworks and actionable recommendations.

• Strong knowledge of metric design, dashboarding, dimensional data modeling, and modern analytics workflows.

• Experience with tools such as dbt, Git, cloud data warehouses, and business intelligence platforms.

• Strong communication and stakeholder-management skills.

• High standards for data quality, rigor, and documentation.

• Experience in healthcare, insurance, care delivery, financial operations, or another operationally complex industry.

• Experience with experimentation, causal inference, predictive modeling, forecasting, or optimization.

• Experience with clinical quality, revenue cycle management, prior authorization, or patient lifecycle data.

• Experience partnering with engineering teams on data architecture, pipelines, or event schemas.

• Familiarity with the data requirements of AI or agentic systems.