Sr Data Scientist - W2 (NO C2C) Posted by Tauqeer

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Description:

This position offers a unique opportunity to apply data science skills at the intersection of healthcare, AI ethics, and regulatory compliance.

Primary 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 Qualifications:

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 Qualifications:

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