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Data Scientist - Healthcare Analytics and AI

Organizational Overview

Ponos Management, LLC specializes in providing compassionate value-based care through a physician driven, home and mobile based model. Our comprehensive care approach integrates social, mental, physical, and economic solutions addressing the unique needs of patients living with complex chronic conditions such as sickle cell disease, Crohn’s disease, ulcerative colitis, and severe rheumatoid arthritis.

Our mission is to reduce emergency room visits and improve the quality of life for our members through coordinated, holistic care delivery. Ponos Care currently operates nationally and continues expanding its innovative value-based care model through clinical partnerships, data driven population health management, and integrated care coordination programs.

Technology, analytics, and digital innovation are central to advancing the organization’s mission and improving outcomes for vulnerable populations.

Position Overview

The Data Scientist – Healthcare Analytics & AI will play a key role in advancing Ponos Care’s mission to become a data-driven, AI-enabled healthcare organization. This role focuses on developing predictive models, advanced analytics, and data-driven insights that support clinical decision-making, improve patient outcomes, and drive value-based care performance.

The Data Scientist will collaborate closely with clinical leadership, engineering teams, and executive stakeholders to design and deploy analytics solutions that help identify, engage, and proactively treat members suffering from inflammatory and immune-related conditions.

This position will contribute to the development of advanced predictive models supporting proactive patient interventions, clinical risk identification, and healthcare utilization optimization across Ponos Care’s Medicaid population.

Core Responsibilities

Develop predictive models and advanced analytics to identify high-risk members and support proactive care interventions.
Contribute to the development of the RAP Early-Warning System to provide 24–72-hour predictions for acute pain crises.
Build analytics models supporting biologics stewardship, including biosimilar adoption and site-of-service optimization.
Develop models to identify chronic kidney disease (CKD) progression risks and enable early clinical intervention.
Analyze healthcare datasets including claims, EHR, pharmacy, and device data to generate actionable insights.
Collaborate with engineering teams to support development of a HIPAA-compliant data lakehouse architecture integrating multiple healthcare data sources.
Implement feature engineering pipelines and support model deployment within modern MLOps frameworks.
Support population health initiatives by analyzing utilization patterns, member demographics, and clinical outcomes.
Ensure analytics solutions comply with healthcare regulatory standards including HIPAA, NCQA, and Medicaid reporting requirements.
Utilize healthcare interoperability standards such as HL7, FHIR, and ADT feeds to integrate and analyze clinical data.

Program Leadership & Strategy:

Establish a multi-year AI and analytics transformation roadmap.
Lead cross-functional collaboration between clinical, operational, and technology teams.
Drive adoption of data-driven decision making across the organization.
Align analytics strategy with value-based payment models and Medicaid performance metrics.

Regulatory & Compliance Oversight:

Ensure compliance with HIPAA, NCQA standards, FDA guidance on clinical decision support tools, and Medicaid reporting requirements.
Support state-specific Medicaid regulatory requirements and value-based payment contract obligations.
Maintain strong data governance practices to protect member privacy and ensure regulatory compliance.

Operational Excellence & Performance Management:

Establish KPIs and analytics dashboards to measure program outcomes and operational performance.
Lead analytics initiatives that improve care coordination, utilization management, and cost containment.
Develop performance reporting frameworks supporting leadership decision making.

Team Leadership & Development:

Build and lead a high-performing analytics and AI team including data scientists, engineers, and informatics specialists.
Foster a culture of innovation, collaboration, and continuous improvement.
Provide mentorship and technical guidance across the analytics organization.

Innovation & Growth:

Position Ponos Care as a leader in AI-driven healthcare innovation within Medicaid populations.
Identify opportunities to scale predictive analytics and AI capabilities across new markets and service lines.
Support research and partnerships advancing AI-driven population health management.

QUALIFICATIONS AND EDUCATION

Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline required.
Master’s degree (MS, MPH, or similar advanced degree) preferred.
Three to six years of experience in data science, machine learning, or advanced analytics.
Experience working with healthcare datasets such as claims, electronic health records (EHR), or pharmacy data strongly preferred.
Experience developing predictive models that support operational, financial, or clinical decision-making.
Experience supporting analytics initiatives in healthcare, Medicaid, value-based care, or managed care environments preferred.
Programming proficiency in Python or R.
Strong SQL and advanced data analysis capabilities.
Experience with modern data architecture including lakehouse environments, data pipelines, and feature stores.
Understanding of machine learning model lifecycle including training, validation, deployment, and monitoring.
Familiarity with MLOps practices and machine learning infrastructure.

Preferred Knowledge

Healthcare interoperability standards including HL7, FHIR, and ADT.
Risk adjustment methodologies including HCC v28 and HCCRx.
Clinical decision support systems and EHR workflows.
Experience supporting analytics in Medicaid populations, population health programs, or value-based care models.

EEO STATEMENT

We are an Equal Opportunity Employer and are committed to fostering an inclusive and diverse workplace. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, sexual orientation, gender identity or expression), national origin, age, disability, genetic information, veteran status, or any other protected characteristic in accordance with applicable federal, state, and local laws.

We believe inclusion strengthens our organization and enhances our ability to serve members and communities nationwide. We are committed to providing reasonable accommodation for qualified individuals with disabilities throughout the recruitment and employment process.

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