Ataraxis AI Inc. logo

Head of Market Access

Job Overview

Location

New York (Remote Possible)

Job Type

Full-time

Category

Other

Date Posted

April 9, 2026

Full Job Description

đź“‹ Description

  • • As Head of Market Access at Ataraxis AI Inc., you will lead the development and execution of payer strategy across Medicare, Medicaid, and commercial payers, playing a critical role in ensuring patients receive optimal cancer treatments through effective reimbursement pathways.
  • • Your day-to-day responsibilities will include leading complex payer negotiations, owning coding and payment strategy, building HEOR analyses and budget impact models, creating field-ready materials for the commercial team, and shaping long-term reimbursement and access strategy for the company’s AI-native oncology tools.
  • • You will join a mission-driven, flat-organization AI precision medicine company at the forefront of healthcare innovation, working alongside leading AI researchers, medical doctors, and industry veterans, with advisors including Yann LeCun and top oncologists from premier cancer research institutions.
  • • In this role, you will have the opportunity to directly impact how cancer is treated by securing favorable payer agreements and innovative payment models, helping Ataraxis achieve its goal of impacting 50% of new cancer cases by 2030 through cutting-edge AI tools like the Ataraxis™ Breast platform.

Skills & Technologies

Remote

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Ataraxis AI Inc. logo
Ataraxis AI Inc.
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About Ataraxis AI Inc.

Ataraxis AI provides AI-powered decision-support solutions for the healthcare industry. Its cloud platform ingests clinical, financial and operational data to predict patient deterioration, optimize staffing and reduce administrative burden. Targeting hospitals and health systems, the company delivers real-time dashboards that rank patients by risk, suggest interventions and quantify financial impact. Ataraxis AI integrates with existing electronic health records and claims feeds, offering explainable models built on de-identified datasets to support clinicians and administrators in improving outcomes and lowering costs.

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