Professional - Data Scientist IV

About the role

The organization is seeking a Lead Data Scientist to support large-scale modernization efforts. The role requires applying advanced data science, natural language processing, and statistical methodologies to legacy claims processing systems.

Responsibilities

- Apply advanced data science and machine learning techniques to analyze, classify, and interpret business rules extracted from legacy claims processing systems. - Design, develop, and validate NLP models for automated parsing of COBOL, ALC, and related legacy code structures. - Perform latent semantic analysis, topic modeling, and other text analytics methods on historic documentation to derive, cluster, and verify business logic. - Lead the statistical validation of extracted rules to ensure accuracy, reproducibility, and alignment with known business processes. - Support the development of a vendor-neutral rules repository by defining data models, ensuring data quality, and advising on scalable ingestion workflows. - Collaborate closely with software engineers, legacy system SMEs, enterprise architects, and modernization teams. - Provide technical leadership on data science best practices, model governance, reproducibility, and deployment pipelines. - Evaluate new AI/ML technologies and propose approaches that improve throughput, accuracy, and automation. - Communicate 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.

Qualifications

- 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, GCP). - Prior experience leading data science teams or mentoring junior data scientists on federal programs.

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, GCP). - Prior experience leading data science teams or mentoring junior data scientists on federal programs.

Benefits

- Medical, dental, vision, life, disability, and other insurance plans. - ESPP (employee stock purchase program). - 401K program with company match. - HSA (Health Savings Account on the HDHP plan). - SupportLinc Employee Assistance Program (EAP) with up to 8 free counseling sessions. - Corporate discount savings program and other discounts. - On-demand training program, certification prep, and a library of technical and leadership courses/books/seminars. - Certification discounts and other perks to associations like CompTIA and IIBA. - Dedicated customer service team for benefits and other resources. - Certified Career Coach.