Cotiviti is a leading solutions and analytics company that leverages financial datasets to deliver deep insight into the performance of retail system. These insights uncover new opportunities for retail organizations to collaborate to improve their financial performance and accuracy along with reducing inefficiencies.
Cotiviti is seeking a hands‑on Data Scientist to build production‑ready machine learning solutions that power the next generation of Retail Technology. You’ll work with large on premise and cloud datasets, apply AI/ML to real-world identification and validation challenges, and collaborate directly with auditors and engineers to deliver high‑impact results. This role is perfect for an ambitious technologist who wants to ship real models—not conduct research—and make a direct impact in a fast‑moving environment.
This role aligns with our Retail Recovery Audit solution. Cotiviti Retail. This role can be located within the US or Canada (Ontario area only)
This job description is intended to describe the general nature and level of work being performed and is not to be construed as an exhaustive list of responsibilities, duties and skills required. This job description does not constitute an employment agreement and is subject to change as the needs of Cotiviti and requirements of the job change.
Mental Requirements:
Physical Requirements and Working Conditions:
Base compensation ranges from $110,000 to $140,000 per year. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs.
Cotiviti offers team members a competitive benefits package to address a wide range of personal and family needs, including medical, dental, vision, disability, and life insurance coverage, 401(k) savings plans, paid family leave, 9 paid holidays per year, and 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti. For information about our benefits package, please refer to our Careers page.
This role is based remotely and all interviews will be conducted virtually.
Date of posting: 03/16/2026
Applications are assessed on a rolling basis. We anticipate that the application window will close on 06/15/2026, but the application window may change depending on the volume of applications received or close immediately if a qualified candidate is selected.
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