Cotiviti

Data Scientist

Job Locations US-Remote
ID 2025-16759
Category
Engineering/IT
Position Type
Full-Time

Overview

Cotiviti is seeking a Data Scientist to lead the development of advanced classification and predictive systems for

healthcare risk adjustment and ICD-10 code classification. This role will focus on building intelligent NLP systems that

analyze clinical charts and encounters to accurately identify and classify ICD-10 codes through sophisticated pattern

recognition, machine learning, and natural language processing techniques. The position includes working on MLOps

and MCP initiatives and will be a key contributor to the Edifecs Business Unit AI innovation project, driving cutting-

edge AI solutions across the healthcare technology portfolio.

Responsibilities

  • Lead development of NLP-based classification systems for ICD-10 code identification from clinical charts and encounters
  • Design and implement deep learning models using PyTorch and transformer architectures for medical text analysis
  • Design and implement Model Context Protocol (MCP) for LLM governance, including model registry, deployment orchestration, and performance tracking systems
  • Implement comprehensive MLOps frameworks including CI/CD pipelines for model deployment, A/B testing infrastructure, and production model monitoring
  • Build and optimize machine learning models for accurate risk adjustment coding and HCC classification
  • Develop decision support systems for automated ICD-10 code suggestion and validation
  • Create and maintain feature engineering pipelines for clinical text processing and model training
  • Implement model evaluation metrics and performance optimization strategies for healthcare coding accuracy
  • Produce comprehensive technical documentation and training materials for NLP models
  • Conduct system health checks and performance monitoring for deployed coding models
  • Collaborate with engineering teams to integrate ML/NLP solutions into production systems
  • Provide technical guidance on statistical modeling, transformer architectures, and algorithm selection
  • Support data pipeline design and implementation for clinical text analytical workflows
  • Participate in code reviews and maintain high standards for code quality
  • Experience with distributed computing frameworks and big data technologies for processing large volumes of clinical data
  • Mentor junior scientists and analysts in machine learning, NLP, and artificial intelligence best practices
  • Track record of using assistive AI technology to improve quality and efficiency of modeling and analytics
  • 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

  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or related field; Master's in Data Science or related field preferred
  • 3+ years of experience in machine learning and AI with focus on NLP, classification, and predictive systems
  • Strong expertise in PyTorch and transformer architectures (BERT, RoBERTa, etc.) for text classification
  • Proficiency in Model Context Protocol design and implementation for enterprise LLM governance
  • Experience with MLOps tools and frameworks (MLflow, Kubeflow, Weights & Biases) and LLM deployment platforms
  • Advanced Python programming skills with experience in NLP frameworks and libraries
  • Experience with healthcare claims data, clinical text processing, and ICD-10 coding systems preferred
  • Knowledge of risk adjustment methodologies and HCC (Hierarchical Condition Categories) coding
  • Experience with feature engineering techniques for clinical text and model evaluation methodologies
  • Experience with model deployment and monitoring in production environments
  • Understanding of data quality frameworks and error detection methodologies for healthcare coding
  • Strong analytical and problem-solving skills with focus on clinical data challenges
  • Excellent communication skills with ability to explain technical NLP concepts clearly
  • Experience with version control systems and collaborative development practices
  • Expertise with SQL and data manipulation tools for healthcare datasets

Cognitive / Mental Requirements:

  • Communicating with others to exchange information.
  • Problem-solving and thinking critically.
  • Completing tasks independently.
  • Interpreting data.
  • Making timely decisions in the context of a workflow.
  • Maintaining focus.
  • Assessing the accuracy, neatness and thoroughness of the work assigned.
  • Learning new tasks and completing tasks in situations that have a speed or productivity quota.
  • Remembering and adhering to processes and protocols.
  • Applying established protocols in a timely manner.

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 high-speed internet access / connectivity and office setup and maintenance.
  • Must be able to provide a dedicated, secure work area.

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.

 

Date of posting: xx/xx/2025

Applications are assessed on a rolling basis. We anticipate that the application window will close on xx/xx/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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