Data Scientist at South Side Healthy Community Organization

South Side Healthy Community Organization

Data Scientist - Data Infrastructure and Analytics

We are seeking a visionary and technical Data Scientist to help lead the transition and development of our in-house predictive analytics platform. As SSHCO enhances its internal data intelligence capabilities, you will be the lead designer of a proprietary suite of AI/ML models focused on health equity and behavioral engagement which is central to our long-term sustainability strategy. You will report to the Director of Health Information Exchange and play a defining role in building a self-sustaining, data-driven healthcare ecosystem.

Key Responsibilities

To perform this job successfully, an individual must be able to perform each essential job function satisfactorily. Reasonable accommodation may be made to enable individuals with disabilities to perform essential duties.

• Collect, clean, and analyze complex datasets from internal and external sources, ensuring data quality and integrity for downstream modeling.
• Manage the end-to-end model lifecycle using MLFlow (or similar tools), including version control, performance monitoring, and detailed documentation.
• Develop predictive and propensity models to optimize member engagement, identifying preferred communication modalities and effective outreach timing.
• Design models that integrate clinical data (e.g., pharmacy claims/Medication Adherence) with non-clinical third-party data (Social Determinants of Health and financial risk factors).
• Establish closed-loop systems that utilize real-world outreach outcomes to iteratively retrain and fine-tune model accuracy.
• Act as the technical lead for program evaluation, using statistical analysis to validate trends, measure intervention impact, and communicate findings to technical and non-technical stakeholders.
• Collaborate with cross-functional teams to design new analytic strategies and data-driven improvements tailored to the South Side community.
• Maintain strict compliance with HIPAA and other data privacy regulations while managing sensitive healthcare and consumer datasets.
• Contribute to grant proposals, research publications, and community reports as needed.
• Stay current with trends in healthcare analytics, data science, and non-profit operations to support the long-term sustainability of the organization.
  
  

Qualifications

• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Public Health, or a related field.
• 2+ years of experience applying data science techniques in healthcare, public health, or non-profit sectors.
• Project management experience and the ability to lead cross-functional teams preferred.
• Strong proficiency in Python/R and SQL for advanced machine learning, data analysis and modeling.
• Experience with MLFlow or similar tools for model registry, versioning, and lifecycle management.
• Expert knowledge of Feature Engineering techniques (dimensionality reduction and scaling), parameter tuning, and predictive modeling.
• Experience building models that integrate clinical data with non-clinical third-party data, with a focus on Social Determinants of Health (SDoH) and financial risk factors.
• Experience building propensity models to optimize member engagement and outreach modality.
• Proven ability to establish outcomes feedback loops to retrain and fine-tune models based on real-world outreach results.
• Experience with data visualization tools like Tableau or Power BI.
• Excellent communication skills, specifically the ability to explain complex model scores to clinical and outreach teams.
• Demonstrated commitment to health equity, social impact, and the mission of non-profit organizations.