Senior Analytics Engineer, Clinical Quality and Outcomes

At LifeStance Health, we strive to help individuals, families, and communities with their mental health needs. Everywhere. Every day. It’s a lofty goal; we know. But we make it happen with the best team in mental healthcare.

Thank you for taking the time to explore a career with us. As the fastest growing mental health practice group in the country, now is the perfect time to join our team!

LifeStance Health Values

Belonging: We cultivate a space where everyone can show up as their authentic self.

Empathy: We seek out diverse perspectives and listen to learn without judgment.

Courage: We are all accountable for doing the right thing - even when it's hard - because we know it's worth it.

One Team: We realize our full potential when we work together towards our shared purpose.

• Benefits
• As a full-time employee of LifeStance Health, the following benefits are offered: medical, dental, vision, AD&D, short and long-term disability, and life insurance. Additional benefits include a 401k retirement savings with employer match, paid parental leave, paid time off, holiday pay and an Employee Assistance Program.

ROLE OVERVIEW

The Senior Analytics Engineer, Clinical Quality and Outcomes supports the Chief Medical Officer organization in building the future state of clinical quality, patient safety, outcomes measurement, and clinical research analytics at LifeStance.

Reporting to Clinical Strategy, this individual contributor will serve as the bridge between clinical stakeholders, executive leadership, and enterprise data teams. The role will transform complex clinical data into trusted, governed, and actionable insights that drive clinical decision-making, enterprise quality improvement, regulatory readiness, and research initiatives.

The ideal candidate combines deep technical expertise in healthcare analytics with the ability to understand end-user needs and translate them into intuitive dashboard experiences, scalable reporting solutions, and research-grade data assets. This individual will be responsible for ensuring data integrity from source systems through executive reporting, enabling consistent metrics that can confidently be reported internally, externally, to payers, regulatory bodies, board committees, and potentially investors.

This role will support LifeStance in establishing the next generation of clinical analytics capabilities through modern data architecture, cloud data warehouses (e.g., Redshift, Snowflake) and SQL data transformations, data quality frameworks, advanced analytics methodologies, and scalable self-service reporting environments.

Consistent with LifeStance’s values, every member of the LifeStance team is expected to support each other and the mission, which may mean participating in projects and initiatives and performing functions and responsibilities not specifically outlined in this job description.

KEY RESPONSIBILITES

Clinical Data & Analytics Strategy

Design, build, and maintain SQL-based data transformations that convert EHR and clinical source data into clean, reliable, analysis-ready datasets that are actionable and translatable to our frontline clinicians

Partner with clinical, operational, and executive leaders to translate clinical questions into measurable analytic requirements, data models, and dashboard experiences, using electronic health record data.

Serve as a trusted thought partner for clinical quality, outcomes measurement, patient safety, regulatory readiness, and research-based reporting initiatives.

Identify emerging opportunities to leverage advancements in analytic AI-enabled quality monitoring, and modern healthcare data platforms in the clinical environment.

Work collaboratively with analytics team members across functions to ensure consistency in practice and reporting across functions: Operations, Clinical Operations, Payor Relations, Business Development

Data Integrity & Governance

Maintain rigorous data quality controls, validation processes, lineage documentation, and metric governance standards to ensure trust in clinical reporting.

Design repeatable testing and reconciliation frameworks that identify discrepancies before they reach operational, executive, board, or external reporting audiences.

Ensure consistency of metric definitions and calculations across dashboards, reports, scorecards, and enterprise reporting environments.

Apply and uphold data security and privacy best practices for healthcare and health research datasets, including data de-identification standards and minimum-necessary use principles

• •Troubleshoot and resolve data quality issues in clinical datasets, performing exploratory analysis and validation to ensure accuracy and consistency of reported metrics
• •Document data models, pipeline logic, and dashboard definitions to support transparency, maintainability, and knowledge-sharing across the analytics team

Collaborate with enterprise data engineering, analytics engineering, and data analysts to align clinical data models with enterprise data architecture and governance standards

Dashboard Architecture & User Experience

Lead the design of intuitive, user-centered dashboard experiences that enable clinicians, medical leaders, operations leaders, and executives to quickly identify insights and take action.

Translate workflow requirements into dashboards that support both operational intervention, strategic decision-making, and quality improvement.

Design reporting experiences that balance flexibility, self-service analytics, and standardized enterprise measures.

Apply user-centered design principles to ensure dashboards are adopted, trusted, and operationally relevant.

Develop executive, board, regulatory, and clinician-facing reporting solutions that provide a consistent source of truth across audiences.

Research & Outcomes Analytics

Build and curate research-grade datasets that support clinical outcomes studies, publication efforts, payer reporting, and real-world evidence generation.

Partner with clinical and research leaders to operationalize outcomes measures, patient-reported outcomes, and quality indicators into analytically rigorous datasets.

Ensure data are appropriately validated, documented, and reproducible for internal and external research use.

Data Engineering & Platform Development

Design and maintain scalable analytics models, data marts, and reporting layers using cloud based data warehouses (AWS Redshift, Snowflake) and modern cloud data architecture.

Develop and optimize SQL-based transformations supporting clinical quality, patient safety, outcomes, and research reporting.

Leverage modern analytics engineering practices. For example: dbt, automated testing, version control, documentation, and CI/CD methodologies.

Collaborate with enterprise data engineering teams to ensure clinical analytics solutions align with enterprise architecture and future-state platform strategy.

REQUIREMENTS

Bachelor’s degree in Data Science, Statistics, Computer Science, Informatics, Engineering, Public Health, or a closely related field.

7+ years of experience in healthcare analytics, analytics engineering, business intelligence, data science, or related disciplines.

5 + years experience working directly with clinical subject matter experts and executive stakeholders to define, refine, and operationalize complex measures.

Demonstrated experience designing enterprise reporting solutions that support executive, operational, clinical, and regulatory decision-making.

Advanced SQL expertise with experience building scalable analytic datasets and reporting environments.

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 ensure reporting accuracy and cons