Data Scientist – Applied AI (LLMs, SLMs & Predictive Modeling)

Overview

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The CenterWell Centralized Data & Analytics team is seeking a highly hands-on Data Scientist 2 to lead the design, development, and scaling of predictive models, LLM- and domain-specific SLM-based solutions, and agentic AI systems for Home Health applications.

This role operates at the intersection of applied AI innovation and real-world production impact, with significant ownership in building production-grade AI systems trained on clinical data. You will combine advanced analytics and machine learning with modern AI techniques, along with strong MLOps, cloud, and Responsible AI practices, to deliver solutions that drive measurable business and patient outcomes.

Key Responsibilities AI Systems & Intelligent Modeling

Own the design and development of end-to-end intelligent systems combining predictive modeling, LLMs, and domain-specific SLMs

Design and deploy predictive models (e.g., classification, regression, ranking, time series forecasting, anomaly detection, churn and risk modeling, and recommender systems), and integrate these signals into LLM- and SLM-based systems (e.g., RAG pipelines, decision engines)

Build and fine-tune proprietary SLMs trained on clinical notes and healthcare corpora

Develop and deploy LLM-based and agentic AI systems for reasoning, automation, and decision support

Engineer and optimize models across structured and unstructured data (tabular, text, and image)

Clinical NLP, Multimodal AI & Innovation

Develop advanced clinical NLP solutions using embeddings, semantic search, and domain-specific models (e.g., ClinicalBERT, PubMedBERT)

Extract insights from large-scale unstructured healthcare data, including clinical text corpora

Build and extend multimodal AI capabilities, including computer vision models (e.g., image classification) as complementary systems

Prototype and explore emerging approaches in LLMs, SLMs, and agentic AI to drive continuous innovation

Translate AI outputs into actionable clinical and business insights

Delivery, MLOps & Impact

Lead end-to-end delivery, from rapid prototyping and MVP development to scalable production systems

Partner with engineering, product, and business stakeholders to align AI solutions with strategic goals

Deploy and monitor ML/LLM/SLM systems, including model performance, drift, bias, and impact

Implement MLOps best practices, including CI/CD, model lifecycle management, and scalable cloud deployment (Azure/AWS)

Drive Responsible AI practices, including explainability, governance, and compliance in healthcare environments

Growth & Impact

Opportunity to shape the direction of applied AI systems in a rapidly evolving healthcare domain

Exposure to cutting-edge techniques across LLMs, SLMs, and agentic AI

Clear path to expanded ownership, technical leadership, and strategic influence

Why This Role

Build real-world AI systems deployed at scale , not just prototypes

Develop domain-specific SLMs on clinical data —a high-impact, differentiated capability

Work on meaningful problems that directly improve patient outcomes in Home Health

Operate at the intersection of predictive AI, SLMs, and agentic systems

Take ownership of solutions that drive measurable business and clinical impact

Required 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 foundations in statistical modeling

Proven experience developing and deploying LLM and/or SLM-based systems in real-world environments

Hands-on expertise fine-tuning domain-specific models (e.g., LoRA, QLoRA, RLHF, DAPT, DPO)

Strong experience in predictive modeling, including feature engineering, validation, and production deployment

Experience working with structured and unstructured data, particularly NLP and text-based systems domain-specific models (e.g., ClinicalBERT, PubMedBERT)

Proficiency with modern AI/ML ecosystems, including Hugging Face, PyTorch/TensorFlow, Databricks, and MLOps practices

Ability to independently own and drive complex AI solutions from concept to production

Preferred Qualifications

Master’s degree in a quantitative or technical field

Experience working with clinical or healthcare data

Exposure to multimodal AI systems (text + image)

Experience developing domain-specific or proprietary language models

Additional Information

You will report to a Lead Data Scientist

Location & Work Style

This role is open to a remote work style in the US

Eastern or Central time zone is preferred

Ability to travel for on-site team meetings (occasionally) on East Coast

Work at Home Guidance

To ensure Home or Hybrid Home/Office associates' ability to work effectively, the self-provided internet service of Home or Hybrid Home/Office associates must meet the following criteria:

At minimum, a download speed of