Professional - Data Scientist IV
Role details
Job location
Tech stack
Job description
This organization is seeking a Lead Data Scientist to join a team of qualified, diverse professionals supporting large-scale modernization efforts. The ideal candidate will serve as a technical leader in applying advanced data science, natural language processing, and statistical methodologies to extract, classify, and validate business rules embedded within legacy claims processing systems. This role is critical in enabling transformation initiatives by ensuring the accurate translation of logic into modern, vendor-neutral rule frameworks., * Applying advanced data science and machine learning techniques to analyze, classify, and interpret business rules extracted from legacy claims processing systems.
- Designing, developing, and validating NLP models for automated parsing of COBOL, ALC, and related legacy code structures.
- Performing latent semantic analysis, topic modeling, and other text analytics methods on historic documentation to derive, cluster, and verify business logic.
- Leading the statistical validation of extracted rules to ensure accuracy, reproducibility, and alignment with known business processes.
- Supporting the development of a vendor-neutral rules repository by defining data models, ensuring data quality, and advising on scalable ingestion workflows.
- Collaborating closely with software engineers, legacy system SMEs, enterprise architects, and modernization teams.
- Providing technical leadership on data science best practices, model governance, reproducibility, and deployment pipelines.
- Evaluating new AI/ML technologies and proposing approaches that improve throughput, accuracy, and automation.
- Communicating analytical findings and model behavior to technical and non-technical stakeholders.
Requirements
- Minimum of 8 years of experience with a BS/BA degree; or 6 years with an MS/MA; or 3 years with a PhD.
- Demonstrated experience leading large-scale data science, NLP, or machine learning projects in enterprise or federal environments.
- Experience analyzing or modernizing legacy systems (COBOL, ALC, mainframe environments) using data-driven or automated approaches.
- Knowledge of agile development methodologies and experience contributing within multidisciplinary teams.
- U.S. Citizenship is required.
Technical Skills:
- Hands-on expertise with NLP techniques including parsing, embeddings, semantic similarity, classification, and information extraction.
- Proficiency with Python and common data science/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, spaCy, Hugging Face).
- A strong statistical background including hypothesis testing, model validation, and performance evaluation methods.
- Proven ability to translate complex analytical findings into clear recommendations for both technical and non-technical stakeholders., * Experience supporting modernization efforts within federal healthcare programs.
- Familiarity with claims processing rules or policy structures.
- Experience building or contributing to knowledge bases or rule repositories.
- Expertise in modernizing legacy systems or supporting migration from mainframe codebases to cloud-native architectures.
- Experience applying AI/ML to large government datasets or regulated healthcare environments.
- Certifications in data science, AI/ML engineering, or cloud platforms (AWS, Azure, Google Cloud Platform).
- Prior experience leading data science teams or mentoring junior data scientists on federal programs.