Principal Quantitative Scientist

LifeStance Health

1d•$140,000 - $160,000•Remote

About The Position

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. ROLE OVERVIEW We are looking for an experienced Quantitative Scientist to join our Analytics and Insights team at LifeStance Health, one of the largest providers of mental health care in the country. Reporting to the VP of Insights and Analytics, this is a high-ownership individual contributor role to lead a robust program of clinical quantitative research on mental health care at national scale. You will work closely with cross-functional stakeholders to define and execute a clinical research roadmap, including publication of peer-reviewed research. You will investigate drivers of clinical quality across a broad spectrum of mental health services and translate findings into tangible improvements in care quality in real-world patients. 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.

Requirements

Master’s degree in a quantitative discipline such as applied statistics, mathematics, biostatistics, data science, epidemiology, health economics and outcomes research, or a related discipline with 10+ years full-time experience conducting quantitative health care research in provider, payor, consulting, or other industry settings, required. Alternatively, a candidate may have a PhD in a quantitative discipline such as applied statistics, mathematics, biostatistics, data science, epidemiology, health economics and outcomes research, or a related discipline and 5+ years full-time experience conducting quantitative health care research in provider, payor, consulting, or other industry settings, 5+ years using open-source programming languages (Python or R) for data cleaning, statistical analyses, data visualization, and generating summary reports, required
Multiple years of experience conducting statistical analyses on real-world clinical data, such as electronic health records, claims databases, observational cohort studies, or clinical trials
Strong quantitative skills in statistical analysis of longitudinal and observational data, with mastery of techniques for related study designs (missing data, propensity score weighting, etc.)
Strong record of peer-reviewed publications from real-world datasets, with additional experience supporting other short-form formats (e.g., blog posts, white papers) with data-driven insights and statistical analysis
Intermediate SQL skills, with 2+ years of experience using SQL to extract and transform extract data from cloud data warehouse
Strong collaboration and communication skills, with clear record of independent stakeholder partnership to iterate on results and align on goals
Applied experience in core principles of machine learning (e.g., cross-validation, model tuning) and building predictive models for clinical use cases
Remote requirements include a quiet, distraction free, dedicated HIPAA (Health Insurance Portability and Accountability Act) compliant workspace in your remote office.
Qualified candidates must be legally authorized to be employed in the United States.
LifeStance is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability, or any other legally protected status.
Demonstrates awareness, inclusivity, sensitivity, humility, and experience in working with individuals from diverse ethnic backgrounds, socioeconomic statuses, sexual orientations, gender identities, and other various aspects of culture.

Nice To Haves

Experience in quality improvement (QI) initiatives, specifically generating insights from real-world clinical data to inform impactful QI initiatives
Experience and related domain expertise in psychiatry, neuroscience, or other related mental health discipline
Strong skills in machine learning and data science, with experience building predictive models deployed for production use cases
Familiarity with AWS tech stack (e.g., Redshift, EC2, S3, etc.)
Experience creating dashboards with business intelligence software, preferably Power BI

Responsibilities

Serve as expert analyst for clinical quantitative research, owning the planning and execution of quantitative analysis to support all clinical research at LifeStance.
Leverage our national data to generate novel research findings on the effectiveness of a broad range of outpatient treatments (e.g., psychotherapy, medication, TMS) across virtual and in-person settings
Implement a variety of statistical approaches tailored for complex research questions, such as longitudinal analysis, survival modeling, multi-level modeling, and predictive modeling.
Extract and transform electronic health record data into structured datasets suitable for research analysis.
Partner with other analysts and data engineering to define reproducible, versioned data assets.
Provide research findings to support validation and dissemination of high-quality mental health care through peer-reviewed research, conference presentations, white papers, and blog posts
Collaborate independently with clinical leaders to plan research initiatives and set priorities according to clinical and business goals
Conduct quantitative analysis to support design of evidence-based quality improvement initiatives (e.g., clinical care pathways, patient-clinician matching, clinical decision support)
Explore opportunities to embed predictive analysis and predictive models into clinical and operational workflows to improve care quality and patient retention