Data Scientist (ML/AI, NLP, Python)| TELECOMMUTE

Data Scientist (ML/AI, NLP, Python) This position offers a unique opportunity to apply data science skills at the intersection of healthcare, AI ethics, and regulatory compliance. Responsibilities:

• Clearly communicate with diverse teams including legal, compliance, and AI development over a wide variety of AI methods including Generative AI and traditional ML.
• Document findings, create reports, and present results to stakeholders.
• Design, and develop job aids and guidance documentation for best practices of responsible AI.
• Develop Python scripts to automate testing processes and analyze results.
• Help identify vulnerabilities related to PII/PHI exposure in AI interactions
• Maintain test data sets and contribute to improving testing methodologies
• Stay abreast of the latest developments in AI/ML research and incorporate relevant findings into work
• Provide mentorship and guidance to colleagues, fostering a culture of continuous learning and improvement
• Assist in designing and executing Red Team testing scenarios for conversational AI systems

Required:

• BS degree plus 3+ years equivalent experience in computer science, applied mathematics, applied statistics, or similar quantitative fields of study
• 3+ years of experience with the full ML system development, deployment, and maintenance lifecycle
• 3+ years of experience working with advanced NLP models and methodologies
• 3+ years of experience with python and ML frameworks (e.g., scikit-learn, Pandas, Numpy)
• Deep understanding of ethical considerations and fairness in AI model development
• Strong analytical thinking and problem-solving abilities
• Excellent written and verbal communication skills

Preferred:

• Familiarity with healthcare systems including claims payment, call centers, or claims-based research.
• Proven ability to translate business needs and requirements into technical solutions
• Proven ability to collaborate effectively with cross-functional teams, including product managers, data scientists, and business stakeholders
• Experience working with large language models or conversational AI systems
• Familiarity with prompt engineering and adversarial testing methodologies
• Exposure to regulatory frameworks relevant to AI in healthcare
• Basic understanding of information security principles