[Hiring] Data Scientist II @Cotiviti

Role Description

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 aligns with our Retail Recovery Audit solution and can be located within the US or Canada (Ontario area only).

• Work with key stakeholders both within R&D and Operations, along with product management to assess the potential value and risks associated with business problems that have the potential to be solved using machine learning and AI techniques.
• Develop an exploratory data analysis approach to verify the initial hypothesis associated with potential AI/ML use cases.
• Document your approach, thinking and results in standard approaches to allow other data scientists to collaborate with you on this work.
• Prepare your final trained model and develop a validation test set for QA.
• Work with production operations to deploy your model into production and support them in monitoring model performance.
• Participate in other data science teams collaborating with your peers to support their projects.
• Participate in knowledge sharing sessions to bring new insights and technologies to the team.
• Participate in design sessions to continuously develop and improve the Cotiviti machine learning platform.
• Provide End to End value-based solutions, including data pipeline, model creation and application for end user consumption.
• Complete all responsibilities as outlined in the annual performance review and/or goal setting.
• Complete all special projects and other duties as assigned.
• Must be able to perform duties with or without reasonable accommodation.

Qualifications

• MS or PhD. Degree in relevant discipline (Math, Statistics, Computer Science, Engineering or Health Sciences) or commensurate professional work experience.
• 4-7 years’ experience in advanced analytics.
• 3+ years’ experience in working in Big Data environments.
• Significant experience with SQL, ability to write SQL queries to efficiently extract data from relational databases.
• Experience developing machine learning models in an exploratory data analytics environment and working with others to develop production ready versions of the models that are deployed within operational environments.
• Experience in using machine learning tools to develop production strength models including, but not limited to, Python, TensorFlow, pandas, numpy, scikit-learn, spark, scala, hive, impala.
• Applied Machine Learning: Application of a variety of machine learning techniques to increase identification of payment integrity issues for our clients, reduce the cost of auditing processes or increase the quality of care and outcomes.
• Big Data Analysis: Strong ability to manage and analyze data in a Big Data environment using a variety of scripts, potentially including but not limited to Scala/Spark and Python as well as Cloud based ML/AI capabilities.

Requirements

• Critical Thinking: Ability to think critically and evaluate information objectively, considering different perspectives and potential implications before drawing conclusions or making recommendations.
• Attention to Detail: Must have a keen eye for detail to ensure accuracy in data analysis, interpretation, and reporting.
• Quantitative Aptitude: Strong numerical skills are essential for conducting quantitative analysis, working with statistical methods and models, and manipulating data using mathematical operations.
• Data Interpretation: Skilled in interpreting data visualizations, charts, graphs, and other forms of data presentation to extract meaningful insights and communicate findings effectively.
• Communication Skills: Effective communication skills are crucial for conveying complex technical concepts and insights to non-technical stakeholders clearly and understandably through written reports, presentations, and verbal discussions.
• Curiosity and Learning Agility: A strong desire to learn and explore new methodologies, techniques, and tools in the field of data analysis and insights generation is essential for staying current with industry trends and best practices.
• Resilience: The ability to handle pressure, adapt to changing priorities, and overcome setbacks is important in a fast-paced and sometimes ambiguous analytical environment.
• Ethical and Integrity: Upholding ethical standards and maintaining integrity in handling sensitive data and information is paramount for building trust and credibility in the insights provided.

Physical Requirements and Working Conditions

• Remaining in a stationary position, often standing or sitting for prolonged periods.
• Repeating motions that may include the wrists, hands, and/or fingers.
• Must be able to provide a dedicated, secure work area.
• Be able to provide high-speed internet access/connectivity and office setup and maintenance.
• No adverse environmental conditions expected.

Benefits

• Base compensation ranges from $110,000 to $140,000 per year.
• 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.

Company Description

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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