Job Description
About The Company CenterWell, a subsidiary of Humana Inc., is dedicated to transforming healthcare delivery for seniors through innovative, personalized care solutions. As a leading provider of senior-focused primary care, home healthcare, and integrated health services, CenterWell emphasizes a holistic approach that addresses physical, emotional, and social wellness. Our mission is to improve health outcomes by providing accessible, comprehensive, and compassionate care tailored to the unique needs of each patient. With a commitment to innovation and excellence, we leverage cutting-edge technology and data-driven strategies to enhance patient experiences and clinical results. Our collaborative, multidisciplinary teams work closely with patients to foster trust, engagement, and long-term well-being, setting new standards in the healthcare industry. About The Role We are seeking a highly skilled and proactive Data Scientist 2 to join our Centralized Data & Analytics team. In this role, you will lead the design, development, and deployment of advanced AI systems, including predictive models, large language models (LLMs), and domain-specific systems (SLMs), tailored for Home Health applications. Operating at the intersection of applied AI innovation and real-world impact, you will have significant ownership in building scalable, production-grade AI solutions trained on clinical data. Your expertise will drive the development of intelligent systems that support reasoning, automation, and decision-making processes, ultimately improving patient outcomes and operational efficiency. This position offers an exciting opportunity to work on transformative healthcare AI initiatives, utilizing your technical skills to create meaningful change in the lives of seniors and healthcare providers alike. Qualifications Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related quantitative field, or equivalent practical experience 4+ years of experience in data science, machine learning, or applied AI with strong statistical modeling foundations Proven experience developing and deploying LLM and/or SLM-based systems in real-world environments Hands-on expertise in fine-tuning domain-specific models (e.g., LoRA, QLoRA, RLHF, DAPT, DPO) Strong background in predictive modeling, feature engineering, validation, and production deployment Experience working with structured and unstructured healthcare data, especially NLP and clinical text systems (e.g., ClinicalBERT, PubMedBERT) Proficiency with AI/ML ecosystems such as Hugging Face, PyTorch, TensorFlow, Databricks, and MLOps best practices Ability to independently lead complex AI solutions from conception through to scalable production Responsibilities Design and develop end-to-end intelligent systems integrating predictive modeling, LLMs, and domain-specific SLMs to support healthcare applications Create and deploy various predictive models including classification, regression, ranking, time series forecasting, anomaly detection, and recommender systems, integrating signals into LLM- and SLM-based pipelines Build and fine-tune proprietary SLMs trained on clinical notes and healthcare corpora to enhance domain-specific understanding Develop LLM-based and agentic AI systems for reasoning, automation, and clinical decision support Engineer and optimize models across structured data, unstructured text, and images, ensuring high performance and scalability Develop advanced clinical NLP solutions utilizing embeddings, semantic search, and domain-specific models like ClinicalBERT Extract actionable insights from large-scale unstructured healthcare data, including clinical texts and imaging Prototype innovative multimodal AI capabilities, integrating text and image data to expand system functionalities Translate AI outputs into practical clinical and business insights to inform decision-making Lead end-to-end delivery of AI projects, from rapid prototyping and MVP development to scalable production systems Collaborate with engineering, product, and business teams to align AI solutions with organizational goals Implement MLOps practices, including CI/CD pipelines, model lifecycle management, and cloud deployment (Azure/AWS) Monitor model performance, detect drift, bias, and evaluate impact, ensuring responsible AI practices Benefits Competitive salary within the range of $97,900 - $133,500 per year, commensurate with experience Bonus incentive plan based on individual and company performance Comprehensive health benefits including medical, dental, and vision coverage 401(k) reti