Sr. Director, Data Science & Analytics

This is a remote position.

Position Summary:

The Sr. Director, Data Science & Analytics is responsible for defining and leading our clients enterprise data science and advanced analytics strategy. This leadership role will focus on developing predictive models, machine learning solutions, and scalable analytics platforms to enable datainformed decisions across the organization. The Senior Director will build and lead a highperforming team that transforms provider and member data into actionable intelligence, supports business innovation, and drives measurable outcomes.

This individual will partner closely with senior leadership, product, operations, growth, data engineering and data governance teams to operationalize insights, optimize business performance, and expand our clients capabilities in artificial intelligence (AI), machine learning (ML), and decision science.

This is a fulltime, exempt, remote position reporting to the Senior Vice President, Data and Analytics.

Base Salary Range: $225,000 to $250,000 annually.

Specific Responsibilities:

Enterprise Data Science Strategy:

• Define and execute a roadmap for enterprise data science that aligns with our clients mission, data strategy, and product portfolio.
  
• Identify key opportunities for predictive modeling, machine learning, and optimization to support provider and member data initiatives.
  
• Lead the development of scalable models, algorithms, and decisionsupport tools to improve operations, data quality, and customer engagement.
  
• Establish best practices for model development, validation, monitoring, and continuous improvement.
  

• Analytics Platform & Capability Development:
  

  • Guide the implementation of a robust, cloudnative analytics environment that enables rapid experimentation and insight generation.
    
  • Drive the development of reusable data products, features, and frameworks that scale across use cases.
    
  • Champion MLOps, automation, and reproducibility for productiongrade model deployment and monitoring.
    

  • Data Insights, BI & Performance Measurement:
    

    • Lead the development of analytics dashboards, KPIs, and visualizations that empower business units to make datainformed decisions.
      
    • Partner with stakeholders to translate complex analytical outputs into business value, actionable insights, and measurable outcomes.
      
    • Standardize and govern enterprisewide analytics metrics and methodologies to ensure consistency and reliability.
      

    • CrossFunctional Collaboration:
      

      • Work closely with Data Engineering, Architecture, and Governance teams to ensure data science solutions are interoperable, secure, and aligned with our clients enterprise data ecosystem.
        
      • Collaborate with product, operations, and growth teams to embed analytics into workflows and externalfacing solutions.
        
      • Partner with external vendors, research institutions, and data providers to expand modeling capabilities and data assets
        

      • Leadership & Team Development:
        

        • Recruit, lead, and mentor a highperforming team of data scientists, ML engineers, and analysts.
          
        • Foster a culture of curiosity, innovation, and continuous learning through coaching, technical leadership, and performance management.
          
        • Build team capacity and maturity across advanced analytics, statistical modeling, and AIML disciplines.
          

        • Supervisory Responsibilities:
          

          • Direct supervision of data science and advanced analytics teams
            
          • Matrix collaboration with data governance, engineering, and product and operations teams.
            
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            Requirements

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            Skills:
            

            • Proven ability to lead enterprise data science strategy and deliver actionable insights that drive business impact.
              
            • Strong expertise in statistical modeling, machine learning, optimization, and data mining techniques.
              
            • Proficiency in Python, R, SQL, Spark, and data science frameworks (e.g., scikitlearn, TensorFlow, PyTorch, XGBoost).
              
            • Experience deploying models in cloud environments (Azure preferred) using MLOps tools and practices.
              
            • Exceptional communication and stakeholder management skills, with the ability to explain complex models and methods to nontechnical audiences.
              
            • Deep understanding of BI, KPI frameworks, and performance measurement.
              
            • Familiarity with data governance and compliance frameworks (e.g., HIPAA, HITRUST, GDPR).
              
            • Knowledge of healthcare data and standards (e.g., FHIR, HL7, X12) is a strong plus.
              

            • Experience:
              

              • 10+ years of experience in data science, analytics, or applied statistics, including 5+ years in a senior leadership role.
                
              • Demonstrated success in building and leading highperforming analytics or data science teams.
                
              • Proven track record in deploying machine learning models in production environments with measurable business outcomes.
                
              • Experience working with large, complex datasets, preferably in healthcare, health tech, or life sciences.
                

              • Education:
                

                • Bachelor’s degree in computer science, data science, statistics, applied mathematics, or a related field required.
                  
                • Master’s or PhD in a quantitative discipline preferred.
                  
                • Certifications in machine learning, data science, or cloud platforms (e.g., Azure) are a plus.
                  
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                  Benefits

                  Our client offers competitive compensation along with an extensive benefits package for all fulltime employees, including medical, dental and vision coverage, tuition assistance and a 401k. They​ offer fulltime remote work to all staff from any location and maintain a physical office in downtown Washington, DC.