Engagement Manager - Healthcare Payment Integrity / AI Analytics

Role Overview Fractal Analytics is a strategic AI partner to Fortune 500 companies. We help enterprises use data, analytics, and AI to improve decisions, operations, and business outcomes. Role Overview We are looking for a hands-on Engagement Manager to lead a strategic healthcare payer analytics engagement focused on Payment Integrity, claims analytics, and AI/ML-led claim review prioritization. This is not a pure project management or account management role. The person must manage client stakeholders and program governance while also contributing hands-on to analytics solution design, model review, validation, and delivery quality. The right candidate should have the technical depth to review analytical approaches, challenge model outputs, understand Databricks-based delivery, guide feature engineering discussions, and explain model results to business stakeholders. Key Responsibilities Client & Stakeholder Management Serve as day-to-day engagement lead and primary point of contact for client stakeholders. Build trusted relationships with Payment Integrity, claims operations, analytics, clinical/coding, audit, SIU, and technology stakeholders. Lead working sessions, weekly governance meetings, executive reviews, and decision forums. Translate client priorities into clear analytical, technical, and delivery actions for Fractal teams. Hands-on Analytics & Technical Delivery Work hands-on with data science and data engineering teams on healthcare claims analytics and AI-led scoring solutions. Review and guide analytical approaches for procedure cohorting, provider benchmarking, anomaly detection, risk scoring, and claim prioritization. Support feature engineering using claim header, claim-line, provider, procedure, billing, and review feedback data. Review model outputs for business usefulness, explainability, false positive patterns, and operational reviewability. Partner with technical leads on Databricks notebooks, pipelines, data profiling, scoring workflows, validation artifacts, and handover documentation. Program Delivery & Governance Own engagement governance, delivery planning, milestone tracking, status reporting, scope management, and risk/issue management. Coordinate onshore and offshore teams to ensure clear ownership and disciplined execution. Prepare weekly status reports, monthly executive summaries, milestone readouts, and scale recommendations. Track team allocation, utilization, budget/resource status, and delivery burn. Validation, Adoption & Scale Lead validation cycles with client reviewers and SMEs. Capture reviewer feedback, false positive themes, reason-code gaps, itemized bill needs, and operational improvement areas. Help refine scoring outputs, reason codes, anomaly flags, claim review rosters, and review recommendations. Connect model outputs to operational impact, workflow adoption, ROI framing, and scale readiness. Must Have Skills 10+ years of experience in analytics delivery, data science delivery, technical program leadership, engagement management, consulting delivery, or similar client-facing roles. At least 5 years of experience in healthcare payer, claims, Payment Integrity, provider analytics, audit, SIU, clinical/coding review, fraud/waste/abuse, or medical cost management. Hands-on experience with analytics, data science, or ML delivery; this role requires technical proficiency, not just program coordination. Strong understanding of healthcare claims data, including claim header, claim-line, provider, procedure, diagnosis, billed/allowed/paid amounts, and review outcome data. Proficiency with Databricks or similar cloud data platforms. Strong working knowledge of SQL and Python; PySpark experience is strongly preferred. Experience with feature engineering, exploratory data analysis, data profiling, model scoring, validation, and analytical QA. Experience with ML methods such as anomaly detection, outlier scoring, provider benchmarking, risk scoring, classification, clustering, or ensemble-based modeling. Ability to review model outputs, identify data/model quality issues, and guide refinement with data science teams. Ability to explain analytical and ML outputs to non-technical business stakeholders. Strong program governance skills, including project planning, RAID management, milestone tracking, executive reporting, and escalation management. Ability to be onsite at client locations in NYC / Connecticut 3-4 days per week. Good to Have Skills Experience with Payment Integrity analytics, itemized bill review, claims editing, provider outlier detection, procedure-level claims analytics, or claim review prioritization. Experience building or guiding ML-led prioritization, anomaly detection, provider benchmarking, reason-code generation, or explainability frameworks. Experience with MLflow or similar model tracking tools. Experience with production-readiness planning, pipeline QA, runbooks, model handover, and operational support. Experience with Snowflake, Azure, AWS, GCP, or similar enterprise data/AI platforms. Experience preparing executive readouts, steering committee materials, ROI narratives, and scale recommendations. Experience managing T&M engagements, delivery financials, resource planning, and commercial governance. Bachelors degree in Business, Engineering, Information Technology, Analytics, Data Science, Healthcare Management, or a related field. MBA or advanced degree is a plus. Pay and Benefits The wage range for this role depends on skill set, experience, certifications, location, and business needs. This role may also be eligible for a performance-based bonus. Full-time employees are eligible for health, dental, vision, life insurance, disability, and 401(k) plans in accordance with plan terms. Fractal also provides paid holidays, parental leave, and a flexible PTO policy. Equal Opportunity Statement Fractal provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment of any type. #J-18808-Ljbffr Fractal