数据科学家 IV
Data Scientist IV
职位概述：
数据科学家IV负责领导先进分析、机器学习和人工智能解决方案的设计、开发和实际应用，以改善医疗运营、患者结果和组织绩效。该职位在涉及预测建模、生成式AI、代理AI、自然语言处理（NLP）和大规模医疗数据科学解决方案的复杂项目中提供技术领导力。他们影响企业AI战略，建立技术标准，并指导数据科学家，同时保持对创新AI和机器学习能力开发的实际贡献。
核心职责：
· 领导从原型到可扩展生产部署的AI和机器学习解决方案的实施。
- 建立技术标准、设计评审、最佳实践和可重用框架，用于AI、机器学习和高级分析解决方案。
- 跟踪最新的大语言模型（LLM）、NLP、生成式AI和医疗信息学趋势，将相关进展整合到项目中，推动持续创新。
- 使用医疗数据源（包括理赔、电子健康记录/电子病历、实验室、使用管理以及其他临床和运营数据集）设计、开发并监督预测建模、机器学习和统计解决方案；确保适当的评估、校准、监控和可解释性。
- 进行严谨的数据分析，包括数据清洗、特征工程和探索性数据分析，以获得有意义的见解和可操作的建议。
- 设计、开发、测试、部署和管理先进的AI解决方案，包括生成式AI、代理AI、NLP、深度学习和检索增强生成（RAG）功能，使用已建立的MLOps和LLMOps实践。
- 在将AI和机器学习解决方案从原型过渡到可扩展生产部署方面提供技术领导。
- 评估新兴AI技术，并根据业务价值、风险和可扩展性推荐企业采用策略。
- 确保符合HIPAA/PHI处理和内部治理标准；与隐私、安全和合规合作伙伴合作，降低数据泄露、提示注入和不安全输出等风险。
- 与跨职能利益相关者（临床领导、风险调整、护理管理、运营、IT和分析合作伙伴）协作。
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Job Summary:
The Data Scientist IV is responsible for leading the design, development, and operationalization of advanced analytics, machine learning, and artificial intelligence solutions that improve healthcare operations, patient outcomes, and organizational performance. This role provides technical leadership across complex initiatives involving predictive modeling, generative AI, Agentic AI, Natural Language Processing (NLP), and large-scale healthcare data science solutions. They influence enterprise AI strategy, establishes technical standards, and mentors data scientists while remaining a hands-on contributor to the development of innovative AI and machine learning capabilities.
Essential Functions:
· Lead the operationalization of AI and machine learning solutions from prototype through scalable production deployment.
- Establish technical standards, design reviews, best practices, and reusable frameworks for AI, machine learning, and advanced analytics solutions.
- Stay current on the latest trends in LLMs, NLP, generative AI, and healthcare informatics, integrating relevant advancements into projects to drive continuous innovation.
- Design, develop, and oversee predictive modeling, machine learning, and statistical solutions using healthcare data sources including claims, EHR/EMR, laboratory, utilization management, and other clinical and operational datasets; ensure appropriate evaluation, calibration, monitoring, and interpretability.
- Conduct rigorous data analysis, including data cleansing, feature engineering, and exploratory data analysis, to derive meaningful insights and actionable recommendations.
- Design, develop, test, deploy, and govern advanced AI solutions including Generative AI, Agentic AI, NLP, deep learning, and retrieval-augmented generation (RAG) capabilities using established MLOps and LLMOps practices.
- Provide technical leadership in transitioning AI and machine learning solutions from prototype to scalable production deployment.
- Evaluate emerging AI technologies and recommend enterprise adoption strategies based on business value, risk, and scalability.
- Ensure compliance with HIPAA/PHI handling and internal governance standards; collaborate with privacy, security, and compliance partners to mitigate risks such as data leakage, prompt injection, and unsafe outputs.
- Collaborate with cross-functional stakeholders (clinical leadership, risk adjustment, care management, operations, IT, and analytics partners) to prioritize work, define KPIs, and communicate results, tradeoffs, and roadmap progress.
- Serve as a subject matter expert for AI, machine learning, and advanced analytics initiatives across the enterprise.
- Perform any other job related duties as requested.
Education and Experience:
· Bachelor's degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or other related field required
- Master's degree preferred
- Equivalent years of relevant work experience may be accepted in lieu of required education
- Eight (8) years of experience in predictive analytics, data science, or a related field, preferably within the healthcare industry or managed care organizations, required
- Three (3) years of technical leadership, solution ownership, or mentoring experience required
- One (1) year of experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflakes) required
- Three (3) years of experience delivering LLM and/or generative AI solutions (e.g., prompt engineering, fine-tuning approaches, and/or RAG) from prototype through production required
Competencies, Knowledge and Skills:
· Technical leadership skills including mentoring, solution architecture, technical review, and ability to influence across cross-functional teams
- Expert knowledge of predictive modeling, machine learning, deep learning, NLP, generative AI, and healthcare analytics methodologies
- Expertise in modern AI architectures including Agentic AI, Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), evaluation methodologies, and techniques for building scalable, trustworthy AI solutions
- Expert knowledge of transformer architectures, deep learning frameworks, and generative modeling concepts, including quality, latency, scalability, and cost tradeoffs
- Familiarity with designing and deploying AI-powered document intelligence, OCR, language extraction, annotation, retrieval, and review workflows utilizing modern NLP, LLM, and Agentic AI technologies
- Familiarity with MLOps/LLMOps practices including CI/CD, experiment tracking, model and prompt versioning, automated testing, monitoring, observability, and reproducible pipelines
- Understanding of AI governance and responsible AI, including privacy-by-design, HIPAA/PHI handling, model risk management, and safeguards against prompt injection and data leakage
- Expert knowledge in SQL and working knowledge of data modeling, data quality, and feature engineering for large healthcare datasets
- Knowledge of healthcare operations, payer and provider models, and industry trends
- Excellent analytical, problem-solving, and critical-thinking skills, including the ability to translate complex data into actionable insights
- Strong project/program leadership skills
- Excellent written and verbal communication and presentation skills
- Knowledge of health care coding including CPT-4, HCPCS, ICD-9/10, DRG and Revenue Codes
- Knowledge of managed care required
Licensure and Certification:· None
Working Conditions:
· General office environment; may be required to sit or stand for extended periods of time
- Ability to travel as required by the needs of the business.
Compensation Range:
$113,000.00 - $197,700.00CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.
Compensation Type (hourly/salary):
SalaryOrganization Level Competencies
- Fostering a Collaborative Workplace Culture
- Cultivate Partnerships
- Develop Self and Others
- Drive Execution
- Influence Others
- Pursue Personal Excellence
- Understand the Business
This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.
Brand=CareSourceOriginally posted on Himalayas