Lead Data Scientist, Causal Inference – Clinical Outcomes Contractor

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🔥 1 minute ago

🇺🇸 United States – Remote

💵 $150 / hour

⏱ Part Time

🟠 Senior

📊 Data Scientist

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Phamily

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Phamily is an industry-leading in-house Chronic Care Management (CCM) and Proactive Care platform. The company supports health systems and medical groups nationwide by launching scalable in-house CCM service lines. This enables proactive patient support between visits and delivers sustainable monthly reimbursement without the need for outsourcing. Phamily is known for its cutting-edge technology that improves patient wellness, delivers superior preventative care, and maximizes organizational sustainability. The platform documents care management seamlessly and provides smart care plan templates. Catering to 20+ specialties across 33 states, Phamily enhances patient experience with high engagement rates and reduces hospitalizations significantly. With Phamily, organizations can manage 500 patients per full-time clinical worker, generating substantial revenue and profit.

📋 Description

• Lead the development and execution of longitudinal, quasi-experimental clinical outcomes studies • Evaluate the effectiveness of APCM and CCM programs using healthcare claims and EHR data • Establish patient cohorts, comparison groups, outcome definitions, and analytical frameworks • Quantify differences in hospitalization rates, readmissions, and post-discharge follow-up outcomes • Develop statistically rigorous, reproducible methodologies suitable for actuarial and clinical review • Apply causal inference techniques, including propensity score matching, inverse probability weighting, and difference-in-differences • Identify and address confounding variables, selection bias, and limitations in observational healthcare data • Develop high-dimensional statistical matching approaches for large, complex datasets • Conduct sensitivity analyses and validate research findings • Analyze healthcare claims, EHR, and patient utilization datasets • Develop and maintain analytical workflows using Python, R, and SQL • Work within data environments including dbt, Amazon Redshift, and Looker • Ensure data integrity, analytical reproducibility, and compliance with PHI security requirements • Produce documented analytical code and reporting assets • Collaborate with the Director of Business Intelligence and internal stakeholders • Engage with healthcare clients, clinical leadership, and actuarial teams • Present statistical findings and clinical outcomes clearly • Develop executive-ready presentations, reports, and supporting documentation • Translate complex findings into business and clinical insights • Review previous vendors’ analytical deliverables and identify reusable methodologies, data assets, and findings • Recommend improvements to analytical processes and study designs • Document methodologies and transfer knowledge to the internal Business Intelligence team

🎯 Requirements

• Extensive professional experience in data science, biostatistics, epidemiology, health economics, or clinical outcomes research • Demonstrated expertise in causal inference and observational study design • Proven experience evaluating healthcare interventions and measuring clinical outcomes • Strong proficiency in Python, R, and SQL • Experience analyzing large-scale healthcare claims and EHR datasets • Deep understanding of propensity score matching, quasi-experimental research methodologies, statistical validation, and confounding adjustment • Ability to independently design and execute technically sophisticated analytical studies • Experience developing statistical methodologies suitable for rigorous clinical, actuarial, or external stakeholder review • Strong understanding of healthcare data privacy, HIPAA, and protected health information requirements • Excellent communication skills, including the ability to present complex findings to nontechnical stakeholders • Advanced degree in Statistics, Data Science, Biostatistics, Epidemiology, Health Economics, or a closely related quantitative discipline • Familiarity with APCM, CCM, and healthcare reimbursement models • Knowledge of dbt, Amazon Redshift, and Looker • Experience supporting health-tech startups or rapidly growing healthcare technology companies • Experience developing executive-level clinical outcomes presentations and client-facing research reports

🏖️ Benefits

• Flexible, part-time engagement • Fully remote work arrangement • Flexible schedule • Opportunity to increase weekly hours as project requirements evolve • Project-based engagement with possibility of extension • Opportunity to contribute to meaningful healthcare research and measurable improvements in patient outcomes

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