Applied AI Scientist IV

This is a fully remote position, open to applicants in United States.

📋 Description

• Set the technical vision and oversee the design, development, and implementation of cutting-edge AI solutions aimed at enhancing healthcare operations, patient outcomes, and overall organizational performance.

• Spearhead the assessment of new AI technologies and formulate strategies for enterprise-wide adoption.

• Process and interpret unstructured healthcare data utilizing NLP and deep learning methodologies.

• Provide technical direction for AI initiatives from conceptualization to large-scale production deployment.

• Shape enterprise AI roadmaps and strategies through technical insight and strategic alliances.

• Develop technical standards, reusable frameworks, best practices, and governance protocols for AI development, deployment, monitoring, and optimization.

• Lead intricate NLP, predictive analytics, and applied AI projects across various business sectors.

• Partner with IT, risk adjustment, program integrity, HEDIS, healthcare operations, finance, and clinical teams.

• Create and execute predictive models, algorithms, and statistical methods using extensive healthcare datasets.

• Define and carry out evaluation strategies for ML and LLM solutions, including quality metrics, bias and safety assessments, and post-deployment monitoring.

• Conduct data cleansing, feature engineering, exploratory data analysis, and thorough data examination.

• Collaborate with stakeholders to establish KPIs, metrics, dashboards, and reports that facilitate decision-making.

• Offer strategic insights to senior leadership based on predictive modeling and data analysis.

• Ensure compliance with HIPAA and PHI regulations, maintain data integrity, model governance, and documentation.

• Act as a subject matter expert in AI, machine learning, NLP, Generative AI, and emerging technologies.

• Mentor Applied AI Scientists, Data Scientists, and technical teams through code reviews, providing technical advice, and making architectural recommendations.

• Assess Responsible AI practices, healthcare AI regulations, and governance standards.

• Perform additional job-related tasks as assigned.

⛳️ Requirements

• A Bachelor's degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or a related discipline is essential.

• Equivalent years of relevant experience may be accepted in place of the required educational qualifications.

• A Master's degree is preferred.

• At least eight (8) years of experience in predictive analytics, data science, or a similar field is necessary.

• A minimum of three (3) years of experience in the healthcare industry is required.

• Three (3) years of experience with cloud services such as Azure, AWS, or GCP and modern data platforms like Databricks or Snowflake is mandatory.

• Three (3) years of experience in developing and implementing NLP and Generative AI solutions within the healthcare sector is required.

• Experience in providing technical leadership, architectural guidance, and mentoring scientific teams is essential.

• In-depth knowledge of Agentic AI, LLM architectures, prompt engineering, Retrieval-Augmented Generation (RAG), evaluation methodologies, and AI solution design is required.

• Advanced expertise in MLOps and LLMOps, including model deployment, monitoring, experiment tracking, reproducibility, CI/CD, and governance is crucial.

• Profound understanding of model risk management, AI governance, Responsible AI, and healthcare AI regulatory considerations is necessary.

• Expert knowledge of statistical learning, machine learning, predictive analytics, and scientific computing using Python and/or R is required.

• Proficient in data manipulation, data visualization, and SQL.

• Capability to perform advanced statistical analysis and modeling, including linear and non-linear regression, sampling, and Markov chains.

• Expertise in designing document intelligence, OCR, and information extraction solutions with modern AI technologies.

• Proficiency in AI solution architecture, API integration, and deployment of production-grade AI applications is essential.

• Comprehensive understanding of healthcare data, including medical and pharmacy claims, EMR, HIE, UM, demographic, and population data.

• Familiarity with healthcare operations, payer and provider models, and industry trends is beneficial.

• Skilled in feature engineering and exploratory data analysis.

• Exceptional analytical, problem-solving, and critical-thinking abilities.

• Strong technical leadership, influence, and program coordination skills.

• Excellent written and verbal communication and presentation abilities.

• Licensure and Certification: None required.

• General office environment; ability to sit or stand for extended periods.

• Occasional travel up to 15% may be necessary.

🏝️ Benefits

• A bonus linked to company and individual performance may be available.

• A comprehensive total rewards package is offered.

• An Equal Opportunity Employer environment focused on belonging and support.

• Up to 15% travel for meetings, training sessions, and conferences may be required.