The Principal Data Scientist Risk will apply knowledge and experience to real world problems and seek to utilize their skills reduce the cost of healthcare and improve health quality and outcomes. With access to dedicated on-premise and cloud based big data solutions, the team can work with a vast amount of structured and unstructured data including claims, membership, physician demographics, medical records and others to begin to solve some of the most pressing healthcare issues of our time. A Data Scientist at Cotiviti will be given the opportunity to work directly with a team of healthcare professionals including analysts, clinicians, coding specialists, auditors and innovators to set aggressive goals and execute on them with the team. This is for an ambitious technologist, with the flexibility and personal drive to succeed in a dynamic environment where they are judged based on their direct impact to business outcomes.

As Principal Data Scientist - Risk within Cotiviti you will be responsible for delivering solutions that help our clients identify payment integrity issues, reduce the cost of healthcare processes, or improve the quality of healthcare outcomes. You will work as part of a team and will be individually responsible for the delivery of value associated with your projects. You will be expected to follow processes and practices that allow risk reviews and documentation of models on our machine learning platform for production execution and monitoring.

• Owns and plans risk/review process for AI solutions across the Enterprise.
• Designs risk and model validation plans with milestones and independent verification.
• Work with key stakeholders within Research and Development as well as 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 Artificial Intelligence techniques.
• Applies appropriate Responsible AI principles, documentation and monitoring process
• Helps plan, manage and execute risk and control delivery of issues, vulnerabilities, control processes, for any Audits
• Assess and drive efficiencies in existing risk framework for Machine Learning Development Lifecycle & MLOps to create a risk aware continuous compliance mind-set
• Identify, implement, establish risk reduction governance to mitigate failed internal processes, inadequate risk identification and controls, and emerging risks
• Plan and perform testing of new functionality and regression testing of technology/risk compliance related requirements
• Partner with cross LOB stakeholders to establish and deliver firm wide control standards and procedures
  including adherence to controls in technology and cyber risk domains ( ex - application security,
  vulnerability management, data management )
• Assess technology and operational risks as AI-ML Technology products evolve with adoption, to effectively define risks and remediation plans
• Provide updates on product/program and create risk management summary reports to senior leaders
• 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. 

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.

• Graduate degree in a quantitative discipline such as Computer Science/Engineering, Statistics, Operations Research covering Advanced Statistics, Machine learning and AI.
• 5+ years of experience in product and technology governance/risk/compliance management in regulated industries ( e.g. healthcare analytics ) in addition to 5+ years as hands on AI/Data Scientist
• Familiar with industry standards, frameworks and recognized best practices such as AIML NIST Framework, PCI, SOC, HIPAA
• Proven experience in business analysis and driving operational change/system development
• Able to identify critical requirements and potential gaps by understanding complex and interdependent processes
• Experience capturing and analyzing requirements (internal and external) and translating them into a viable product through agile development is a must
• Able to build strong partnerships with technical teams
• Strong understanding of risk and control management (e.g. technology, data, cyber and operational)
• Experience working with technical teams in complex program execution environment
• Experience with the latest techniques in natural language processing including transformers, LLMs,
  measuring/benchmarking with tools such as HuggingFace, Langchain, LLAMA/Mistral and OpenAI, vector databases from risk perspective.
• 5+ years of hands-on data science/AI experience, using typical machine learning and data science tools
  including pandas, scikit-learn, keras, nltk, and TensorFlow/PyTorch, GPU is preferred.
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
• Experience communicating technical concepts to non-technical and technical audiences is a plus.
• Passion for collaboration, learn it all mindset and driving value with AI.

Mental Requirements: 

• Ability to work independently as well as collaborate as a team with a sense of urgency.
• Professional with ability to properly handle confidential information.
• Be value-driven, understand that success is based on the impact of your work rather than its complexity or the level of effort.
• Ability to handle multiple tasks, prioritize and meet deadlines.
• Ability to work within a matrixed organization.
• Proficiency in all required skills and competencies above.
• Communicating with others and teamwork.
• Assessing the accuracy, neatness, and thoroughness of the work assigned.

Physical Requirements and Working Conditions: 

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

Pay Transparency:

Base compensation ranges from $195,000.00 to $235,000.00. Specific offers are determined by various factors, such as experience, education, skills, certifications, and other business needs. This role is eligible for discretionary bonus consideration.

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.

Since this job will be based remotely, all interviews will be conducted virtually.

Date of posting: 04/25/2025

Applications are assessed on a rolling basis. We anticipate that the application window will close on 06/25/2025, 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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