• Five or more years of professional experience in data science, applied machine learning, artificial intelligence, advanced analytics, healthcare analytics, or a related quantitative or technical role.
• Demonstrated hands-on experience developing, evaluating, deploying, monitoring, or supporting production AI or machine-learning solutions.
• Experience evaluating generative AI, large language model, or conversational AI systems using methods such as evaluation frameworks, scenario-based testing, automated or human review, prompt experimentation, and controlled testing of model or configuration changes.
• Strong proficiency in Python and SQL, including experience developing data pipelines, advanced analytics, machine-learning models, or AI-based solutions.
• Strong foundation in statistical modeling and experimental design, including the ability to establish performance metrics, analyze results, and determine whether changes produce meaningful improvements.
• Experience working with large-scale datasets and cloud-based AI or machine-learning platforms, with familiarity with modern development, deployment, MLOps, or LLMOps practices.
• Ability to assess complex technical systems, diagnose performance issues, and translate findings into practical and measurable improvements.
• Strong written and verbal communication skills, including the ability to collaborate acrosstechnical and operational teams and explain findings, risks, and recommendations toleadership.

Additional Preferred Qualifications

• Hands-on experience with voice agents, conversational AI, natural language processing, agentic AI, or other generative AI applications.
• Experience supporting conversational AI across development, evaluation, deployment, production monitoring, and continuous improvement.
• Experience with AI evaluation approaches such as rubric-based scoring, human evaluation, LLM-as-judge, A/B testing, canary releases, or similar methodologies.
• Experience analyzing voice-agent performance, including transcripts, audio signals, intent recognition, task completion, escalation, transcription quality, and latency.
• Experience with prompt development, retrieval-augmented generation, tool use, knowledge sources, and conversational workflows.
• Experience working in healthcare or another regulated environment, including familiarity with responsible AI, privacy, security, and the handling of PHI, PII, or other sensitive information.
• Experience with R or another statistical programming language.
• Experience providing technical leadership or mentoring technical professionals.

Knowledge Skills and Abilities (KSAs)

• Exceptional verbal and written communication skills, with the ability to translate complex data science concepts into strategic business initiatives and influence stakeholders.
• Strong interpersonal skills with demonstrated leadership and mentorship capabilities.
• Expertise in advanced analytical techniques, problem-solving, and model evaluation, in addition to strong story-telling and trobleshooting skills.
• Advanced proficiency in programming languages such as Python and SQL, as well as expertise in specialized machine learning frameworks including but not limited to TensorFlow or PyTorch.
• Ability to communicate and present technical concepts to executive-level and cross-departmental audiences, including creating dashboards to aid in explaining analytics.
• Expertise in leading-edge data visualization tools and techniques, in addition to a strong understanding of charts, dashboards, and reporting tools.
• Exceptional attention to detal.
• Ability to lead and influence key business initiatives through positive relationships, effective communication, and cross-team colloboration.

Job Duties

• Leads and strategically directs the design, deployment, and evaluation of computational algorithms and predictive models across multiple business units, while overseeing junior data scientists on these projects.
• Researches and implements cutting-edge maching learning techniques and statistical tests to drive innovation in healthcare analytics by staying updated with current academic and industry trends.
• Establishes best practices for team in data science and software development, including version control, testing, and containerization, ensuring deployable models and repeatable analyses across teams.
• Develops internal training programs and guidelines as the quantitative subject matter expert (SME), providing mentorship to junior data scientists and guiding the team in project/program design, statistical methodology, and model interpretation.
• Aligns data science goals with business objective, working directly with business partners in project scoping, timeline management, and documentation.
• Influences organizational strategies through regular engagement, communication, and high-level presentations to both internal and external stakeholders.
• Authors technical reports, statistical analysis plans (SAP), white papers, and peer-reviewed publications as needed.
• Oversees the entire data pipeline, from acquisition to analytics, ensuring data quality and governance standards, and guiding junior team members in these processes.
• Performs other related duties as assigned.

The above statements describe the general nature and level of work only. They are not an exhaustive list of all required responsibilities, duties, and skills. Other duties may be added, or this description amended at any time.

Remains knowledgeable on current federal, state and local laws, accreditation standards or regulatory agency requirements that apply to the assigned area of responsibility and ensures compliance with all such laws, regulations and standards.

Physical and Environmental Demands

Sedentary Work - Exerting up to 10 pounds of force occasionally (Occasionally: activity or condition exists up to 1/3 of the time) and/or a negligible amount of force frequently (Frequently: activity or condition exists from 1/3 to 2/3 of the time) to lift, carry, push, pull, or otherwise move objects. Sedentary work involves sitting most of the time but may involve walking or standing for brief periods of time. Jobs are sedentary if walking and standing are required only occasionally, and all other sedentary criteria are met.

Normal routine involves no exposure to blood, body fluid or tissue and as part of their employment, incumbents are not called upon to perform or assist in emergency care or first aid.

The incumbent has no occupational risk for exposure to communicable diseases.

Because the incumbent works within a healthcare setting, there may be occupational risk for exposure to hazardous medications or hazardous waste within the environment through receipt, transport, storage, preparation, dispensing, administration, cleaning and/or disposal of contaminated waste. The risk level of exposure may increase depending on the essential job duties of the role.

Are you ready to make a difference? Apply Today!

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