Business Intelligence and Analytics Lead

Sagility is a trusted partner for healthcare operations transformation, helping organizations unlock value across complex healthcare workflows. With more than 25 years of healthcare domain expertise, Sagility combines deep operational knowledge with AI-enabled technology and intelligent automation to improve efficiency, strengthen decision-making, and elevate experiences for members, patients, providers, and stakeholders across the healthcare ecosystem. Sagility’s capabilities span end-to-end healthcare operations, including claims administration, payment integrity, clinical and care management support, member and provider engagement, revenue cycle services, and advanced analytics. Today, nearly

50,000 specialists, clinicians, technologists, and operations professionals support healthcare organizations globally through trusted collaboration and technology-led transformation. The Lead BI Programs and Analytics is responsible for defining, developing, and delivering enterprise data products including Business Intelligence dashboards, reporting solutions, and AI/ML-driven insights. The role acts as the bridge between business stakeholders and technical teams to translate business needs into scalable data and analytics solutions. This role owns the end-to-end lifecycle of BI and data products, from ideation to deployment and adoption, ensuring high data quality, strong governance, and measurable business value.

Key Responsibilities: 1.Ideate

• Identify and prioritize high-value data and analytics opportunities.
• Engage business stakeholders and application owners to understand reporting, analytics, and decision-support needs.
• Facilitate requirement gathering workshops and document business problems and objectives.
• Conduct independent research to identify opportunities for BI, analytics, and AI/ML-driven insights.
• Assess potential business impact, ROI, and operational value of proposed data products.
• Prioritize initiatives across dashboards, reporting, advanced analytics, and AI/ML use cases. 2.Explore
• Translate business requirements into a high-level data and technical solution.
• Define business KPIs, metrics, and analytical dimensions in alignment with enterprise definitions.
• Map required data sources and datasets needed to support analytics use cases.
• Collaborate with data engineering teams to define data models and pipeline requirements.
• Identify opportunities for predictive or prescriptive analytics and collaborate with AI/ML teams on feasibility.
• Define integration architecture between source systems, data platforms, BI tools, and AI/ML solutions.
• Provide high-level effort estimation, timelines, and implementation approach. 3. Proof of Concept & Project Management
• Validate ideas through prototypes and early experimentation.
• Define scope for POC, MVP, or prototype dashboards and models.
• Work with BI developers, data engineers, and data scientists to build prototypes.
• Validate KPI definitions, data availability, and dashboard design.
• Demonstrate prototypes to stakeholders and collect feedback.
• Refine scope and solution design based on user feedback and feasibility.
• Coordinate with BI development team for BI and data products, including data validation, functional testing, and UAT. 4. Stakeholder Management & Communication
• Drive adoption of dashboards, reports, and analytics solutions across business teams.
• Conduct user training and enablement sessions.
• Maintain continuous engagement with business users, application owners, and technical teams.
• Monitor usage, gather feedback, and continuously improve the data product.
• Track and communicate business impact of deployed analytics solutions 5. Data Governance & Quality
• Own and maintain master data definitions, hierarchies, and standards used in analytics solutions.
• Ensure alignment with enterprise data governance policies and frameworks.
• Collaborate with data stewards to ensure data quality, consistency, and reliability.
• Define and enforce standards for KPI definitions, reporting logic, and data usage.

Key Skills & Competencies: Functional

• Business Intelligence and analytics product management
• KPI definition and performance measurement frameworks
• Dashboard design and data storytelling
• Business requirement analysis and prioritization Technical:
• BI platforms such as Power BI, Tableau, or similar tools
• Data warehousing, data lakes, and ETL pipelines
• Analytics and AI/ML concepts
• Data integration and enterprise data architecture Behavioral:
• Strong stakeholder management and communication
• Strategic thinking and problem solving
• Cross-functional collaboration
• Ability to translate business problems into data solutions

Qualifications & Experience

• Bachelor’s or master’s degree in business, Data Analytics, Computer Science, or related field
• 7–10 years of experience in BI, analytics, or data product management
• Experience working with cross-functional teams including BI developers, data engineers, and data scientists
• Experience in Agile or product-based development environments preferred