Data Scientist Senior; Population Health

Job Summary

The Senior Data Scientist is a strategic leader in our organization, driving the entire lifecycle of data science initiatives that directly impact healthcare outcomes. Leveraging your deep expertise and mastery of machine learning, you will spearhead the development, implementation, and evaluation of complex AI models in healthcare settings specifically population health. Your ability to translate technical concepts into actionable insights will empower stakeholders to make informed decisions that enhance patient care and operational efficiency.

You will also play a crucial role in mentoring and developing junior data scientists and analysts, fostering a culture of data‑driven innovation.

Location:

Work from home (Pennsylvania).

• Lead and manage the entire lifecycle of data science projects, from conceptualization and design to development, deployment, and ongoing optimization.
• Build and deploy advanced analytics that explain and predict acute utilization (Inpatient/Emergency Department) and quantify how care delivery changes impact outcomes for heart failure and other high‑risk populations.
• Translate longitudinal patient care data into actionable intervention points across primary care, specialty care, and monitoring programs.
• Partner with clinical and operational leaders to convert analytic findings into care pathway recommendations, operational triggers, and monitoring protocols; define measures of success and evaluate impact.
• Collaborate with cross‑functional teams to define project scope, objectives, analytic design, validation strategy, and expected impact, ensuring alignment with organizational goals and measurable improvements in healthcare outcomes.
• Use deep understanding of machine learning algorithms to build patient‑level and population‑level models that support risk stratification, trajectory analysis, forecasting, capacity planning, and scenario analysis for diverse healthcare applications.
• Apply clustering, dimensionality reduction, and deep generative models to uncover hidden patterns and insights within large, complex healthcare datasets.
• Implement rigorous validation techniques to ensure model accuracy, stability, fairness, generalizability, and clinical usefulness across patient cohorts, sites, time periods, and operational settings.
• Oversee the deployment of models into production environments, ensuring seamless integration with existing systems.
• Extract insights from clinical and operational data sources (Epic Clarity, HL7, and other enterprise data sources) to inform decision‑making and guide project direction.
• Translate complex technical findings into compelling narratives that resonate with non‑technical stakeholders through presentations, dashboards, technical documentation, and stakeholder discussions.
• Mentor and guide junior data scientists, fostering their professional growth and technical expertise.
• Promote a culture of collaboration, knowledge sharing, and continuous learning within the data science team.
• Contribute to developing best practices and standards for data science and machine learning within the organization.
• Stay abreast of the latest advancements in machine learning and healthcare research to identify opportunities for improvement and innovation.

• Minimum of 4 years of relevant experience in data science or related field.
• Bachelor's degree in a related field of study is required.
• Strong analytical thinking and statistical methods.
• Proficiency in Python, SQL, and advanced statistical analysis.

• Experience with Databricks, Python, SQL, and advanced statistical analysis.
• Machine learning expertise, including emerging AI technologies and implementation (LLMs, RAG, GenAI, agentic workflow integrations).
• Population health initiatives experience.
• Familiarity with Epic Clarity, Caboodle, claims data, CMS/Medicare populations, or payer‑provider analytics.

• Certification(s) and license(s) are not required but are considered a plus where applicable.

• Analytical thinking
• C++ programming language
• Clinical data cleaning
• Communication
• Group collaboration
• Machine learning methods
• Python (programming language)
• Statistical methods
• Structured Query Language (SQL)

We are an affirmative action, equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.