Senior Healthcare Data Analyst

Job description

Weekly outpatient therapy isn't always enough, and a trip to the ER isn't the only answer. Patients and their families rely on Compass Health Center when in crisis – every day, we help people overcome depression, anxiety, suicidality, obsessions/compulsions, trauma, chronic pain, and other obstacles in order for our patients to live freely. **About This Role** The Senior Healthcare Data Analyst is a senior individual contributor responsible for clinical, outcomes, and program analytics across the organization. This role partners with clinical, operational, and executive leaders to turn complex questions into clear, meaningful insights. A strong understanding of behavioral health care delivery is important, including the patient journey from referral and intake through admission, treatment, utilization, outcomes, and discharge. The role also helps advance AI-enabled analysis within the Data Analysis function, using AI to improve the speed, depth, and efficiency of analytical work while establishing repeatable methods, validating outputs, and ensuring appropriate human and clinical oversight. **What You'll Do** **Healthcare Analytics & Insights** - Analyze access, conversion, census, capacity, utilization, length of stay, patient engagement, clinical outcomes, and program performance. - Develop a strong understanding of behavioral health care delivery, including intake, treatment planning, group, individual and family therapy, psychiatry, documentation, authorization, outcomes, and discharge. - Partner with clinical leaders to understand operational and clinical questions and translate them into meaningful analysis. - Ensure findings reflect how care is actually delivered and are interpreted in the right clinical and operational context. - Identify trends, patterns, risks, and opportunities that can improve care delivery, patient experience, or program performance. - Turn complex findings into clear insights, recommendations, and actions for clinical and executive audiences. - Work independently on complex analytical questions and bring forward recommendations, not just findings. **Clinical Outcomes Research, Program Evaluation & Publications** - Partner with clinical and research leaders to define research questions, outcomes measures, analytical approaches, and data requirements for clinical studies and program evaluations. - Build accurate, well-documented, and reproducible datasets and analyses for outcomes research, program evaluation, presentations, and publications. - Conduct and interpret analyses that evaluate patient outcomes, treatment effectiveness, program effectiveness, and differences across populations, programs, or levels of care. - Work with clinical subject matter experts to ensure findings are interpreted appropriately and limitations are clearly understood. - Translate findings into publication-ready tables, visualizations, summaries, and supporting materials for presentations, abstracts, manuscripts, and publications. - Support analytical review through final presentation or publication, including refining analyses, responding to questions, and reproducing results as needed. - Ensure research and publication-related data and analysis follow organizational privacy, compliance, governance, and data-use standards. **Analytics Partnership & Standards** - Serve as a trusted analytics partner to clinical, operational, and executive leaders. - Help stakeholders clarify questions, define meaningful measures, and translate needs into analytical approaches. - Establish and maintain trusted metric definitions, documentation, analytical standards, and best practices. - Partner with other analysts and Data Engineering to support consistent definitions, reliable data, and scalable solutions. - Move recurring analytical needs into standardized dashboards, reports, or repeatable workflows. - Help stakeholders understand what the data shows, what it does not show, and how it should be interpreted. - Identify opportunities to improve analytical methods, tools, workflows, and how the organization uses data. - Provide subject matter expertise and mentor other analysts as appropriate. **AI-Enabled Analysis & Validation** - Apply and help advance AI-enabled analytical methods within the Data Analysis function. - Identify analytical workflows where AI can improve the speed, depth, quality, or efficiency of analysis. - Use AI to accelerate data exploration, analytical development, quality review, synthesis, and interpretation while independently validating final outputs. - Develop repeatable AI-assisted analytical workflows, methods, prompts, standards, and validation practices. - Validate AI-generated findings for accuracy, relevance, bias, and appropriate clinical or business context. - Ensure human judgment remains accountable for final analytical conclusions. - Partner with clinical subject matter experts when findings require additional clinical interpretation. - Partner with Technology and Data Engineering to evaluate AI capabilities and determine how they can be incorporated into governed analytical workflows. **What You'll Do** - Bachelor’s degree in Analytics, Statistics, Information Systems, Healthcare Administration, Health Informatics, Public Health, or a relevant clinical discipline such as Psychology, Social Work, Counseling, Nursing, or a related field; equivalent relevant experience may be considered. - 5+ years of experience in analytics, healthcare analytics, business intelligence, or related analytical work. Candidates with a clinical background should also have demonstrated experience using data to evaluate care delivery, patient outcomes, program performance, or other complex healthcare questions. - Experience working with healthcare clinical operations and translating clinical workflows and business questions into meaningful analysis. - Experience analyzing healthcare performance, including access, utilization, quality, outcomes, or program effectiveness. - Experience with modern analytics and BI platforms such as Power BI. - Strong analytical skills and the ability to independently investigate complex clinical and operational questions. - Ability to translate complex data into clear insights for clinical, operational, and executive audiences. - Experience using AI or generative AI to support analytical work, with an understanding of how to validate outputs and appropriately manage the risks and limitations of AI-generated analysis. - Strong communication, prioritization, facilitation, and stakeholder partnership skills. - Understanding of healthcare privacy,