Director, LTC Fraud Strategy & Analytics
Listed on 2026-02-21
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IT/Tech
Data Analyst, Data Science Manager, AI Engineer
The Long-Term Care Anti-Fraud, Waste, and Abuse Analytics Director serve as the voice of business and the customer for the fraud component of Claims focusing specifically on designing and developing controls. Accountable for driving new fraud control development which are integrated through the claims process (initiation through ongoing reimbursement), instituting transformational practices, tools, and AI solutions to prevent and detect controls proactively.
This role and the associated squads directed by this role play a critical component in the strategy, vision, outcomes, and key results by aligning and prioritizing business goals with actionable results. With that in mind, Bachelor’s or Master’s degree in Business Administration, Statistics, Mathematics, Data Science, Actuarial Science, or a related field is required. Candidates with other educational backgrounds may also be considered if they demonstrate strong business acumen in these areas.
Equivalent combinations of education and experience will be considered for applicants with relevant, domain‑specific expertise.
The candidate will bring a senior-level strategic view and tactical delivery of products, tools, controls, and business processes aligned to fraud prevention and detection. The candidate is accountable for ideating and prioritizing the work across the Analytics and IT squads to design, test and execute data-driven strategies.
The ideal candidate will bring:
Strategic Vision: Ability to connect the dots across multiple functional areas, anticipate capacity needs, and align team efforts with outcomes.
Operational Excellence
:
Proven ability to optimize processes, manage resources, and drive efficiency across complex workflows.
Analytical Acumen: Strong analytical thinking with the ability to interpret data, identify trends, and translate insights into actionable controls.
AI & Data Science Fluency: Familiarity with emerging technologies, including artificial intelligence, machine learning, and data science methodologies to inform decision-making and innovation.
Project Management Expertise: Demonstrated success in leading cross-functional initiatives, managing timelines, budgets, and stakeholder expectations.
Leadership: Energize and elevate the team and foster a culture of engagement and accountability. This individual should be able to prioritize the most valuable work and drive results. The ideal candidate will inspire trust, align the team around shared goals, and cultivate an environment where people feel valued, motivated, and empowered to contribute their best.
Executional Discipline: Maintain and update key planning tools weekly such as roadmaps, JIRA boards, and status trackers, sponsor decks to ensure transparency, accountability, and momentum across teams.
Position Responsibilities- Drives the strategy, planning, prioritization, roadmap, and delivery of key Fraud capabilities with business partners.
- Acts as a thought partner to business stakeholders on multi-million-dollar Fraud priorities.
- Provide expert insights and recommendations to support strategic decision‑making and risk management.
- Stay updated on industry trends, emerging fraud schemes, and advancements in fraud detection technologies.
- Collaborate with AI to design and develop predictive models to identify potential fraud.
- Analyze large datasets to uncover patterns, anomalies, and trends indicative of fraudulent activities.
- Identify cross‑squad dependencies and impediments to achieving outcomes.
- Collaborate with cross‑functional teams, including data scientists, claims specialists, Call Center, and IT, to integrate fraud detection models into existing systems.
- Collaborate with technical partners to monitor and evaluate model performance ensuring ongoing adjustments to improve detection rates and reduce false positives.
- Mentor and guide junior team members, fostering a collaborative and innovative work environment.
- Bachelor’s or Master’s degree in Business Administration, Statistics, Mathematics, Data Science, Actuarial Science, or a related field. Candidates with other educational backgrounds may also be considered if they demonstrate strong business…
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