Senior Analytics Engineer, Clinical Quality and Outcomes

BEHAVIORAL HEALTH PRACTICE SERVICES; United States; On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

AD&D

Disability insurance

Life Insurance

401k with employer match

Paid parental leave

Paid time off

Holiday pay

Employee Assistance Program

Job summary

LifeStance Health is seeking a Senior Analytics Engineer, Clinical Quality and Outcomes to bridge clinical needs with data platforms. You will transform complex clinical data into trusted insights, design scalable dashboards, and enable decision-making across executive leadership, payers, and regulators.

The role emphasizes data integrity, governance, and collaboration with enterprise data teams to advance clinical analytics capabilities using modern architectures and cloud warehouses.

Qualifications

• Translate clinical questions into measurable analytic requirements and dashboards.
• Turn clinical data into trusted, governance-ready analytics assets.
• Partner with clinical and executive leaders to drive quality improvement.

Responsibilities

• Design, build, and maintain SQL-based data transformations from EHR and clinical data.
• Collaborate with clinical, operational, and executive leaders on analytic requirements.
• Ensure data quality, lineage, and metric governance across dashboards and reports.
• Support data integrity with testing, reconciliation, and validation.
• Assist in scalable self-service reporting and research data assets.

Skills

Data storytelling

Stakeholder collaboration

End-user focus

Tools

SQL

Redshift

Snowflake

ETL tooling

Job description

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