Data Scientist - LLM, Agentic AI & Predictive Modeling

CenterWell

1d • Remote

About The Position

The Data Scientist 2 – LLM, Agentic AI & Predictive Modeling is a hands-on role focused on designing, deploying, and scaling predictive models, LLM-based, and agentic AI solutions in enterprise environments. The role combines advanced analytics, machine learning, and generative AI with strong MLOps, cloud deployment, and Responsible AI practices to deliver production-ready solutions that drive measurable business and customer impact.

Requirements

• Bachelor's degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or related quantitative field.
• 4+ years of hands-on experience in data science, machine learning, or advanced analytics
• Experience with language model fine-tuning
• Experience working with structured and unstructured data, including feature engineering and model development
• Experience building and deploying predictive models to support business decision-making
• Experience applying statistics, modeling, and analytics to translate complex data into insights, reports, and presentations
• Familiarity with LLMs, NLP, or generative AI and their application to enterprise use cases
• Working knowledge of MLOps, cloud platforms, and production deployment practices
• Ability to operate independently, make sound technical decisions in ambiguous situations, and collaborate across teams

Nice To Haves

• Master's degree
• Healthcare experience

Responsibilities

• Identify, design, and implement AI use cases leveraging LLMs, Agentic AI, generative AI, predictive modeling, machine learning, deep learning, and advanced analytics.
• Develop, fine-tune, and deploy LLM-based and agent-based systems for enterprise use cases such as conversational AI, workflow automation, reasoning systems, and decision support.
• Design and deploy predictive models including: Classification, regression, and ranking models, Time series forecasting, Anomaly and fraud detection, Churn, propensity, and risk models, Recommender systems and uplift modeling.
• Translate predictive model outputs into actionable business signals, integrating them into downstream systems, dashboards, and AI-driven workflows.
• Engineer, train, and validate machine learning and deep learning models in Python for both structured and unstructured data, including tabular, text, and image data.
• Apply feature engineering, model calibration, interpretability, and performance optimization techniques to predictive models.
• Combine predictive models with LLMs and agentic systems (e.g., predictive scoring feeding agent decisions or RAG pipelines).
• Apply NLP techniques such as text mining, semantic search, sentiment analysis, embeddings, and knowledge graph construction.
• Build and deploy computer vision and multimodal models, including image classification, object detection, semantic segmentation, and visual search using PyTorch, TensorFlow, Keras, and OpenCV.
• Lead hands-on execution for rapid prototyping, MVP development, and scaled production delivery of identified opportunities for predictive analytics, LLMs, and agentic AI that deliver measurable business value.
• Collaborate cross-functionally with data engineering, product, and business teams to ensure solutions meet operational and strategic goals.
• Deliver clear insights, recommendations, and technical guidance to support enterprise AI adoption.
• Experience deploying and monitoring predictive, LLM, and deep learning models, including performance, drift, bias, explainability, and business impact, using advanced metrics and A/B testing.
• Knowledge of MLOps, cloud platforms, and Responsible AI, including CI/CD, model lifecycle management, Docker/Kubernetes deployment, and enterprise governance across Azure/AWS/GCP.

Benefits

• medical
• dental
• vision benefits
• 401(k) retirement savings plan
• time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
• short-term and long-term disability
• life insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level