药房欺诈项目经理
Pharmacy Fraud Program Manager
职位描述
关于这个职位:
药房欺诈项目经理是特别调查部门的一员,负责检测、验证和调查药房福利中的可疑欺诈行为,包括开药、配药和药房理赔活动,涉及各种内部和外部数据源。该职位的核心是严格的数据验证——从多个系统中协调、交叉核对并压力测试信息,以确认准确性,发现不一致之处,并建立有说服力的调查结果。
理想的候选人应具备深入的好奇心和调查思维,同时具备强大的分析能力,并拥有真实的药房专业知识:精通药房理赔数据和药房福利运营,包括NCPDP理赔字段、NDC、数量和天数供应逻辑、处方集和事先授权概念,以及处方医师和药房标识符(NPI、DEA、州执照),同时还应了解监管框架中有关药房欺诈、浪费和滥用的相关规定。
他们能够熟练识别药房欺诈的触发因素和预警信号——如开药和配药的异常情况、管制药品和过度使用模式、药房计费方案等,并积极利用人工智能辅助的检测和验证工具来扩展分析范围,优先处理案件并减少误报。这个人能够提出困难的问题,跟随数据去向,并将复杂的发现转化为清晰、可操作的结论。
除了欺诈项目经理的核心职责外,该职位还负责与我们的药房福利管理商之间的CFWA关系,协调组织与CVS之间的转介、报告和监督活动。此人将与欺诈项目经理共同合作,进行整体欺诈检测和方案识别。
你的职责和影响将包括:
CFWA关系管理 — CVS
- 作为与CVS的CFWA项目的首要联系人和关系负责人,管理日常协调、升级和信息交换。
- 管理CFWA转介的接收、分发和处理,跟踪每个转介直至解决,并确保按时完成和文档标准符合要求。
- 主导定期的CFWA治理接触点(例如联合运营和工作组会议),
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Job Description
A bit about this role:
The Pharmacy Fraud Program Manager is a member of the Special Investigations Unit responsible for detecting, validating, and investigating suspected fraudulent activity within the pharmacy benefit — including prescribing, dispensing, and pharmacy claims activity — across a wide range of internal and external data sources. This role centers on rigorous data validation — reconciling, cross-referencing, and stress-testing information drawn from numerous systems to confirm accuracy, surface inconsistencies, and build defensible investigative findings.
The ideal candidate pairs a deeply inquisitive, investigative mindset with strong analytical discipline and brings genuine pharmacy depth: fluency with pharmacy claims data and pharmacy benefit operations, including NCPDP claim fields, NDCs, quantity and days supply logic, formulary and prior authorization concepts, and prescriber and pharmacy identifiers (NPI, DEA, state license), together with a working knowledge of the regulatory framework governing pharmacy fraud, waste, and abuse.
They are fluent in recognizing pharmacy fraud triggers and red flags — prescribing and dispensing outliers, controlled substance and overutilization patterns, and pharmacy billing schemes — and they actively leverage AI-assisted detection and validation tools to scale their analysis, prioritize cases, and reduce false positives. This person is comfortable asking hard questions, following the data wherever it leads, and translating complex findings into clear, actionable conclusions.
In addition to the core responsibilities of the Fraud Program Manager role, this position serves as the primary owner of the CFWA relationship with our pharmacy benefit manager, coordinating referrals, reporting, and oversight activities between the organization and CVS. This person will work side by side with the Fraud Program Manager on overall fraud detection and scheme identification.
Your responsibilities and impact will include:
CFWA Relationship Management — CVS
- Serve as the primary point of contact and relationship owner for the CFWA program with CVS, managing day-to-day coordination, escalations, and information exchange.
- Manage the intake, routing, and disposition of CFWA referrals to and from CVS, tracking each referral through resolution and ensuring turnaround times and documentation standards are met.
- Lead recurring CFWA governance touchpoints (e.g., joint operating and workgroup meetings), setting agendas, tracking action items, and driving issues to closure.
- Review CVS-provided FWA reporting, investigative summaries, audit results, and recovery activity for completeness, accuracy, and consistency with source claims data; challenge findings that are not supported by the data.
- Monitor CVS performance against contractual, delegated, and regulatory FWA obligations; identify gaps, request corrective action, and escalate deficiencies to compliance and leadership.
- Track pharmacy-level actions performed by CVS under the PBM agreement — including pharmacy audits, prepayment review, claim edits, recoveries, and network termination — confirming that agreed actions were taken and applied correctly, and escalating where they were not.
Data Validation & Source Reconciliation
- Validate, reconcile, and cross-reference data drawn from numerous and disparate sources — pharmacy and medical claims systems, PBM data feeds, prior authorization and rejected-claim data, eligibility and enrollment systems, prescriber and pharmacy provider files, third-party databases, public records, watchlists, internal applications, and external vendor feeds.
- Identify discrepancies, anomalies, and inconsistencies across data sets — including NDC, quantity, days supply, DAW, prescriber NPI, DEA number, and dispensing pharmacy mismatches — and determine whether they indicate error, manipulation, or fraud.
- Establish and maintain data integrity standards for investigations, ensuring findings are accurate, complete, and defensible.
- Trace data lineage across internal systems and PBM-supplied files, corroborating information against authoritative sources to confirm or refute investigative hypotheses.
AI-Assisted Detection & Validation
- Use AI- and machine learning–driven detection tools to flag suspicious patterns, score risk, and surface high-priority cases for review.
- Validate AI-generated alerts and model outputs against source claims and clinical data, distinguishing genuine fraud indicators from false positives, data artifacts, and legitimate clinical variation.
- Provide structured feedback to analytics, vendor, and PBM partners to improve model accuracy, tuning, and rule logic over time.
- Stay current on emerging AI-enabled fraud schemes (e.g., synthetic identities, deepfakes, generated prescriptions or prior authorization documentation, fraudulent e-prescribing credentials) and adapt detection approaches accordingly.
Pharmacy Fraud Detection, Triggers & Red Flags
- Apply deep knowledge of pharmacy fraud triggers, red flags, and typologies — including prescribing and dispensing patterns — to proactively identify suspicious activity before it escalates.
- Develop, refine, and document indicators and detection criteria based on emerging schemes and investigative learnings.
- Investigate referrals and self-sourced leads, building complete case referrals supported by validated evidence.
Case Referrals
- Conduct thorough data validation into suspected fraudulent activity, documenting methodology, findings, and conclusions.
- Maintain accurate, audit-ready case records in the case management system.
- Prepare clear written summaries and present findings to leadership, business partners, legal, and, when appropriate, law enforcement or regulatory bodies.
Collaboration & Mentorship
- Partner with claims, payment integrity, underwriting, compliance, legal, and data teams — as well as pharmacy operations and clinical and pharmacy services — to share intelligence and strengthen controls.
- Work and collaborate with the Fraud Program Manager on overall fraud detection and scheme identification.
- Mentor junior analysts on data validation techniques, investigative methodology, and red-flag recognition.
- Contribute to continuous improvement of SIU processes, tools, and detection capabilities.
Required skills and experience:
- Bachelor's degree in Criminal Justice, Finance, Data Analytics, Health Administration, Pharmacy, Business, or a related field — or equivalent investigative experience.
- 5+ years of experience in fraud investigation, financial crime, pharmacy benefit or claims analysis, or a closely related field, ideally within an SIU or comparable environment.
- Demonstrated experience with pharmacy claims data and pharmacy benefit operations, including familiarity with NCPDP claim fields, NDCs, formulary and prior authorization concepts, and prescriber/pharmacy identifiers (NPI, DEA, state license).
- Demonstrated experience validating and reconciling data across multiple, disparate systems and sources.
- Experience managing or supporting a vendor, PBM, or delegated-entity relationship, including referral coordination, reporting review, and performance follow-up.
- Strong working knowledge of pharmacy fraud triggers, red flags, and common fraud schemes, and of the regulatory framework governing pharmacy FWA.
- Hands-on experience using analytical, detection, or case management tools, including AI/ML-assisted detection platforms.
- Excellent analytical, critical-thinking, and problem-solving skills, with a naturally inquisitive and skeptical approach.
- Strong written and verbal communication skills, with the ability to present complex findings clearly and concisely.
Desired skills and experience:
- Professional certification such as CFE (Certified Fraud Examiner), CFCS, AFE, AHFI, CPhT, or equivalent.
- Direct experience with CVS/Caremark data, reporting, or FWA processes.
- Experience with controlled substance monitoring, opioid overutilization programs, or PDMP data.
- Experience working with data visualization tools, or analytical querying of large data sets.
Salary range: $73,000 - $130,000 / year
The pay range listed for this position is the range the organization reasonably and in good faith expects to pay for this position at the time of the posting. Once the interview process begins, your talent partner will provide additional information on the compensation for the role, along with additional information on our total rewards package. The actual base salary offered will depend on a variety of factors, including the qualifications of the individual applicant for the position, years of relevant experience, specific and unique skills, level of education attained, certifications or other professional licenses held, and the location in which the applicant lives and/or from which they will be performing the job.
Our Total Rewards package includes:
- Employer sponsored health, dental and vision plan with low or no premium
- Generous paid time off
- $100 monthly mobile or internet stipend
- Stock options for all employees
- Bonus eligibility for all roles excluding Director and above; Commission eligibility for Sales roles
- Parental leave program
- 401K program
- And more....
*Our total rewards package is for full time employees only. Intern and Contract positions are not eligible.
Founded in 2017, Devoted Health is on a mission to dramatically improve the health and well-being of older Americans by caring for everyone like they are family, and that includes our employees. Our robust and seamlessly integrated care platform merges advanced data and AI access with world-class clinical and service experiences to create a member experience that is unlike the industry norm. To continue building upon our mission, we want to bring together those who share our values, embrace change and advancement, and are enthusiastic about where we're going — all the while bringing their own unique qualities, experiences, and expertise, in hopes of further changing the healthcare experience.
Devoted is an equal opportunity employer. We are committed to a safe and supportive work environment in which all employees have the opportunity to participate and contribute to the success of the business. We value diversity and collaboration. Individuals are respected for their skills, experience, and unique perspectives. This commitment is embodied in Devoted’s Code of Conduct, our company values and the way we do business.
As an Equal Opportunity Employer, the Company does not discriminate on the basis of race, color, religion, sex, pregnancy status, marital status, national origin, disability, age, sexual orientation, veteran status, genetic information, gender identity, gender expression, or any other factor prohibited by law. Our management team is dedicated to this policy with respect to recruitment, hiring, placement, promotion, transfer, training, compensation, benefits, employee activities and general treatment during employment.
Originally posted on Himalayas