Senior Analytics Engineer, Clinical Quality and Outcomes

LifeStance Health

4d•$132,000 - $145,000

About The Position

The Senior Analytics Engineer, Clinical Quality and Outcomes supports the Chief Medical Officer organization in building LifeStance Health’s clinical quality, patient safety, outcomes measurement, and clinical research analytics capabilities. Reporting to Clinical Strategy, this individual-contributor role bridges clinical stakeholders, executive leadership, and enterprise data teams. It transforms complex clinical data into trusted, governed, actionable insights for clinical decision-making, quality improvement, regulatory readiness, and research. The role combines healthcare analytics expertise with an understanding of end-user needs to deliver intuitive dashboards, scalable reporting solutions, and research-grade data assets. It is responsible for ensuring data integrity from source systems through executive reporting, enabling consistent metrics for internal and external audiences, including payers, regulatory bodies, board committees, and potentially investors. The position supports modern analytics capabilities using cloud data warehouses, SQL transformations, data quality frameworks, advanced analytics methods, and self-service reporting.

Requirements

Bachelor’s degree in Data Science, Statistics, Computer Science, Informatics, Engineering, Public Health, or a closely related field.
At least 7 years of experience in healthcare analytics, analytics engineering, business intelligence, data science, or a related discipline.
At least 5 years of experience working directly with clinical subject matter experts and executive stakeholders to define, refine, and operationalize complex measures.
Demonstrated experience designing enterprise reporting solutions for executive, operational, clinical, and regulatory decision-making.
Advanced SQL expertise, including building scalable analytic datasets and reporting environments.
At least 5 years developing Power BI or equivalent business intelligence solutions.
Strong experience with Snowflake and modern cloud-based data platforms.
Experience implementing data quality testing, metric validation frameworks, and governance approaches that support reporting accuracy and consistency.
Experience translating stakeholder requirements into usable, impactful dashboard experiences.
Strong understanding of healthcare data structures, electronic health record systems, clinical workflows, and quality metrics.
Legal authorization to work in the United States.
Awareness, inclusivity, sensitivity, humility, and experience working with people from diverse backgrounds and cultures.

Nice To Haves

Experience supporting behavioral health analytics, patient safety programs, measurement-based care, quality improvement, or regulatory reporting initiatives.
Experience developing datasets for peer-reviewed publications, clinical research, outcomes research, or real-world evidence generation.
Experience with dbt, Git, automated testing frameworks, semantic modeling, and modern analytics engineering practices.
Experience with PHQ-9, GAD-7, safety planning, suicidality measures, HEDIS, CMS metrics, accreditation standards, or quality reporting programs.
Experience creating executive-level scorecards and board-facing dashboards.
Master’s degree or higher in Public Health, Data Science, Biostatistics, Informatics, Health Services Research, or a related field.

Responsibilities

Design, build, and maintain SQL-based transformations that convert EHR and clinical source data into reliable, analysis-ready datasets.
Partner with clinical, operational, and executive leaders to translate clinical questions into analytic requirements, data models, and dashboard experiences.
Advise on clinical quality, outcomes measurement, patient safety, regulatory readiness, and research-based reporting.
Identify opportunities to use AI-enabled quality monitoring and modern healthcare data platforms.
Collaborate with analytics teams across Operations, Clinical Operations, Payor Relations, and Business Development to promote consistent practices and reporting.
Maintain data quality controls, validation processes, lineage documentation, and metric governance standards.
Build repeatable testing and reconciliation frameworks to detect discrepancies before reporting.
Ensure consistent metric definitions and calculations across dashboards, reports, scorecards, and enterprise reporting.
Apply healthcare data security and privacy practices, including de-identification standards and minimum-necessary use principles.
Troubleshoot clinical data quality issues through exploratory analysis and validation.
Document data models, pipeline logic, and dashboard definitions.
Collaborate with data engineering and analytics colleagues to align clinical data models with enterprise architecture and governance standards.
Design user-centered dashboards that help clinical, medical, operations, and executive audiences identify insights and take action.
Translate workflow requirements into dashboards for operational intervention, strategic decision-making, and quality improvement.
Balance flexibility and self-service analytics with standardized enterprise measures.
Develop consistent reporting solutions for executives, boards, regulatory audiences, and clinicians.
Build and curate research-grade datasets for clinical outcomes studies, publications, payer reporting, and real-world evidence generation.
Partner with clinical and research leaders to operationalize outcomes measures, patient-reported outcomes, and quality indicators in analytically rigorous datasets.
Validate, document, and support reproducibility of data for internal and external research use.
Design and maintain scalable analytics models, data marts, and reporting layers in cloud data warehouses and modern cloud architectures.
Develop and optimize SQL transformations for clinical quality, patient safety, outcomes, and research reporting.
Use modern analytics engineering practices such as automated testing, version control, documentation, and CI/CD.
Work with enterprise data engineering teams to align clinical analytics solutions with enterprise architecture and platform strategy.
Support LifeStance’s mission and team initiatives, including functions and responsibilities that may not be specifically outlined in the job description.