Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 60 health plans, including many of the top 20, and representing more than 160 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs.
Machinify is seeking a Director, New Product Research & Development to serve as the Healthcare Payment Integrity Subject Matter Expert embedded within our Product organization.
You will partner primarily with Product Management, Data Science, and Engineering to turn domain insight into platform-informed product requirements, model evaluation criteria, and high-impact features. You will also be the Product team’s market and regulatory research engine—continuously translating policy and market dynamics into actionable opportunities and risks. A strong, hands-on understanding of a Payment Integrity platform (e.g., Cotiviti, Machinify) and direct experience working with Data Science are required.
What you’ll do
Lead domain strategy within Product
Define the domain vision and standards for Payment Integrity across prepay and postpay use cases, aligning clinical, coding, and policy rigor with Machinify’s product strategy and business goals.
Help establish governance for policy/clinical accuracy, model and rule validation, and compliance-by-design; set the quality bar and go/no-go criteria for releases.
Platform-first discovery and solutioning
Develop deep expertise in Machinify’s platform capabilities (data ingestion/normalization, rules/decisioning, model training/evaluation, reviewer workbench, explainability/audit, X12/EDI integrations).
Use platform capabilities to drive concept ideation and solution design, recommending configure-vs-build paths to accelerate delivery and scalability.
Partner hands-on with Data Science
Define ground-truth labeling guidance, sampling strategies, and evaluation metrics (precision/recall, dollar yield, false positive rate, overturn rate, provider abrasion).
Review and critique features and model outputs; identify failure patterns and recommend model, rule, or policy adjustments.
Maintain curated test sets and UAT plans that reflect NCCI edits (PTP/MUE), DRG/APC logic, CMS NCD/LCD, plan-specific rules, and fraud/waste/abuse patterns.
Be the market and regulatory intelligence engine
Monitor and synthesize CMS updates (IPPS/OPPS), NCD/LCD, NCCI, state regulations, payer policy trends, provider billing behaviors, and the vendor/competitive landscape.
Deliver concise POVs and impact briefs; translate shifts into product opportunities, risks, and design constraints to inform PM-led prioritization and long-term bets.
Bridge SME Operations insights into product decisions
Aggregate and structure inputs from SME Operations, client services, and customers into prioritized problem statements and actionable requirements that improve model accuracy, reviewer efficiency, and auditability.
Support cross-functional execution and enablement
Participate in requirement reviews, design critiques, and readiness checks; oversee UAT to ensure features meet acceptance criteria and compliance needs.
Conduct trainings and workshops that upskill Product, Engineering, and Data Science on domain concepts and platform implications; create clear domain documentation.
Measure outcomes and iterate
Define domain-level OKRs and success metrics with PM and DS (e.g., yield, accuracy, time-to-detect, overturns, provider abrasion) and drive continuous improvement through analytics and qualitative feedback.
Provide executive-level communication, influence, and stakeholder management across Product leadership and with strategic customers and partners.
Note: This role is focused on product discovery, domain strategy, requirements, and validation. It does not manage day-to-day operations queues, staffing, or customer support.
What you'll need:
Experience
10+ years in healthcare with 7+ years focused on Payment Integrity, claims analytics, medical coding/audit, or payer operations at a health plan, PI vendor, or consultancy.
4–6+ years leading cross-functional domain initiatives or teams; experience hiring, mentoring, and setting standards for SMEs/analysts.
3+ years partnering directly with Data Science and Engineering on data-driven products; health tech experience required.
Strong, hands-on experience with a Payment Integrity platform (e.g., Machinify or comparable) and demonstrated ability to drive configure-vs-build decisions.
Domain knowledge
Deep understanding of claims data and adjudication flows, including X12/EDI (837P/I/D, 835), CARC/RARC, billing guidelines, and payer policy.
Strong grasp of coding and regulatory standards: ICD-10-CM/PCS, CPT/HCPCS, DRG/APC, NCCI (PTP/MUE), CMS NCD/LCD, IPPS/OPPS, and relevant state regulations; familiarity with FWA concepts a plus.
Knowledge of compliance, privacy, and auditability requirements (HIPAA/PHI handling, explainability, traceability).
Product and data skills
Expert at validating user stories, acceptance criteria, decision tables, and comprehensive test plans; proficient with Jira
Data fluency: able to interpret analytics dashboards, partner on experiments, and evaluate model/rule performance with DS.
Collaboration and communication
Executive presence with excellent facilitation and written communication; able to translate complex policy into clear product decisions for technical and non-technical audiences.
Proven track record influencing PM-led prioritization and aligning Engineering and DS around domain-driven requirements.
Education and credentials
Bachelor’s degree in health administration, informatics, nursing/clinical discipline, public health, or related field required; advanced degree preferred.
Relevant credentials such as CPC, CCS, RHIA/RHIT, RN, or similar are preferred.
Traits
Strategic, analytical, and pragmatic; low-ego collaborator who seeks clarity, challenges assumptions, and advocates for users.
Outcome-oriented with high ownership; balances domain rigor with product velocity; comfortable operating at both executive altitude and hands-on detail.
Equal Employment Opportunity at Machinify
Machinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace.
See our Candidate Privacy Notice at: https://www.machinify.com/candidate-privacy-notice/
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