Senior Data Analyst, Network Optimization

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for a Senior Data Analyst, Network Optimization based in the United States. Join a mission-driven virtual healthcare organization working to make high-quality mental healthcare more accessible through technology, data, and innovative clinical solutions. As a Senior Data Analyst, you will play a strategic role in optimizing the clinician network to ensure that patient demand is matched with the right providers, across markets and care programs. You will transform complex, multi-source datasets into actionable insights that guide recruitment, onboarding, clinician retention, and network capacity planning. Working closely with Network Operations, Clinical, Product, and Engineering teams, you will help improve the clinician experience and strengthen patient access to timely, effective care. You will develop forecasting models, evaluate experiments, and establish measurement frameworks that connect operational performance with clinical quality and business outcomes. You will also contribute to a modern, AI-powered analytics ecosystem that improves data reliability and enables faster, more informed decision-making. This remote opportunity is ideal for an experienced analytics professional who combines technical excellence, strategic thinking, and a passion for solving complex problems in a fast-paced healthcare environment.

Build, maintain, and continuously improve forecasting models that compare clinician network capacity with patient demand across all 50 U.S. state markets and multiple clinical care programs. Translate supply-and-demand forecasts into strategic recommendations on where and when to invest in clinician recruitment and network expansion. Partner with Network Operations and Clinical Talent teams to develop analytical frameworks, performance metrics, and insights that improve clinician recruitment, onboarding, engagement, and retention. Design and implement measurement frameworks to evaluate clinical quality, therapeutic alliance, patient-clinician relationships, and patient panel balance at both the clinician and market levels. Collaborate with Product and Engineering teams to design, execute, and evaluate experiments involving patient scheduling experiences and clinician-facing product features. Serve as the primary analytics partner for the Network product team, investigating performance trends, identifying root causes, and connecting key metrics to organizational objectives, clinical outcomes, and financial performance. Present analytical findings, forecasting insights, and experiment results to senior leadership and cross-functional stakeholders, translating complex analyses into clear, actionable business recommendations. Contribute to the development of AI-powered analytics infrastructure by building, maintaining, and documenting data models that support key performance indicators, governed metrics, and AI-assisted analytical workflows. Strengthen data quality, consistency, and reliability by establishing robust metric definitions, testing standards, documentation practices, and scalable data modeling approaches. Leverage AI tools and Model Context Protocol (MCP) integrations to accelerate data exploration, analytical workflows, insight generation, and decision-making. Solve ambiguous business and operational problems using structured analytical methods, creative thinking, and scalable solutions. Collaborate with stakeholders across Network, Clinical, Product, Engineering, and Data teams to identify emerging needs, prioritize analytical initiatives, and support continuous improvement. Requirements At least eight years of professional analytics experience, combined with a master's degree or equivalent practical experience. Expert-level SQL skills and strong data modeling expertise in a cloud-based data warehouse environment, such as Google BigQuery or Google Cloud Platform (GCP). Demonstrated ability to write clean, efficient, performant, and well-documented code that supports reliable analytical workflows. Hands-on experience developing and scaling dbt projects, including data testing, documentation, model development, and governed metric definitions. Strong expertise in forecasting, econometric modeling, and quantitative analysis, ideally complemented by operations research techniques such as capacity planning, supply-and-demand optimization, and resource allocation. Experience designing, executing, and interpreting A/B tests and other experiments, with the judgment to select appropriate alternative evaluation methods when controlled experiments are not feasible. Proficiency in data visualization and business intelligence tools, such as Tableau, with the ability to develop informative dashboards and communicate analytical findings effectively. Familiarity with AI-powered analytical tools and MCP integrations, with a demonstrated habit of using AI to improve data exploration, analysis, and insight generation. Excellent written and verbal communication skills, including the ability to explain complex technical concepts and business implications to audiences ranging from engineers to executives. Strong business judgment and the ability to connect analytical findings with operational priorities, organizational objectives, clinical outcomes, and financial performance. A proactive, self-directed approach to work, with the ability to establish priorities, navigate ambiguity, and deliver results in a dynamic, fast-moving environment. Strong cross-functional collaboration skills and the ability to build trusted relationships with stakeholders across technical, clinical, operational, and product teams. Preferred qualifications: Experience working in healthcare, digital health, or a related clinical services environment. Experience working in interdisciplinary teams that combine technical, operational, clinical, and business expertise. Previous experience in a startup or high-growth organization, particularly in an environment where analytical processes and data infrastructure are evolving rapidly. Interest in using advanced analytics and AI-enabled tools to improve healthcare operations, provider experiences, and patient access to care. Benefits Competitive compensation: Salary based on experience, expertise, geographic location, and other relevant factors. Equity opportunities: Stock options or equity participation, providing an opportunity to share in the organization's long-term growth. Comprehensive healthcare coverage: Fully employer-paid medical, dental, and vision insurance. Pet insurance: Coverage options to help support the health and well-being of your pets. Life and disability insurance: Life insurance, short-term disability, and long-term disability coverage. Retirement savings: Access to a 401(k) retirement plan. Flexible time off: Unlimited paid time off and sick leave. Parental leave: Leave benefits to support employees and their families during important life transitions. Fully remote work: Work remotely from within the United States, offering flexibility in your work environment. Additional perks and memberships: Access to supplementary memberships and other employee benefits. Mission-driven culture: An opportunity to contribute to improving access to mental healthcare and supporting better patient outcomes through data-driven innovation. Inclusive workplace: A collaborative environment that values diverse backgrounds, perspectives, skills, and professional experiences.