Senior Healthcare Data Scientist - AI​/ML

Overview

Position Overview

CINQCARE is redefining how health and care are delivered, starting where trust begins: the community. The Senior Healthcare Data Scientist will be a key member of the Analytics & AI team, responsible for designing and delivering advanced machine learning and analytics solutions that directly inform CINQCARE’s personalized care programs and outreach. This role blends technical expertise with strategic impact — developing predictive models, managing full model life cycles, and translating data into actionable insights that guide engagement, care delivery, and organizational decision-making.

The Senior Healthcare Data Scientist will also drive innovation by testing emerging techniques and ensuring all solutions meet CINQCARE’s standards for equity, fairness, and health impact.

• Design, curate, and maintain analytical datasets by integrating EHRs, claims, engagement data (e.g., Salesforce Health Cloud), third-party SDOH sources, and commercial data (e.g., Neustar, Acxiom).
• Build, evaluate, and manage predictive models (classification, regression, NLP, time series, survival analysis, agentic modeling) to stratify risk, improve targeting, and predict engagement.
• Manage the full model lifecycle — from development through deployment, monitoring, retraining, and drift detection — ensuring production reliability.
• Apply fairness, bias mitigation, and explainability frameworks to ensure models are equitable and trustworthy.
• Use What-If scenario modeling and simulations to support clinical and business decision-making.
• Integrate engagement data into continuous feedback loops that refine model performance and responsiveness.
• Translate complex analyses into clear, compelling stories and insights for clinicians, engagement teams, executives, and community leaders.
• Develop dashboards, reports, and self-service analytics tools for use across CINQCARE teams.
• Partner with engineering teams for scalable deployment using modern MLOps practices.
• Collaborate cross-functionally with clinicians, engagement specialists, and leadership to ensure data science aligns with CINQCARE’s purpose and performance priorities.
• Research, test, and apply emerging methods (e.g., generative AI, causal inference, federated learning) relevant to community-based care and health equity.

• Master’s or PhD in Data Science, Statistics, Computer Science, Economics, or related quantitative field;
  Bachelor’s with significant applied experience considered.
• Minimum 7 years of applied data science experience, ideally in healthcare, public health, insurance, or digital health.
• Demonstrated ability to design, deploy, and manage predictive models in production.
• Strong expertise in Python, SQL, and ML frameworks (scikit-learn, XGBoost, Tensor Flow, PyTorch).
• Experience with NLP, time series modeling, and advanced MLOps practices.
• Familiarity with cloud platforms (Azure preferred; AWS/GCP acceptable).
• Proficiency with visualization tools (Tableau, Power BI, Plotly, Dash).
• Exceptional communication and data storytelling skills for technical and non-technical stakeholders.
• Purpose-driven mindset with demonstrated ownership, accountability, and ability to thrive in collaborative, cross-functional teams.

At CINQCARE, we care for our team like we care for our patients—holistically. We offer flexible, comprehensive benefits so you can thrive while delivering top-notch care.

• Medical Plans:
  Two comprehensive options offered to Team members.
• 401K: 4% employer match for your future.
• Dental & Vision:
  Flexible plans with in-network savings.
• Paid Time Off:
  Generous PTO, holidays, and wellness time.
• Extras:
  Pet insurance, commuter benefits, mileage reimbursement, CME for providers, and company-provided phones for field staff.

The working environment includes in-office work performed indoors in a traditional office setting with conditioned air, artificial light, and an open workspace. You will need to communicate with customers, vendors, management, and co-workers in person and over devices, sometimes with people who are agitated. Regular use of the telephone and e-mail for…