Data Scientist - LLM, Agentic AI & Predictive Modeling

Become a part of our caring community
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.

Key Responsibilities
LLM, Agentic AI & Predictive Modeling

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.

Structured & Unstructured Data Modeling

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).

NLP, Multimodal & Computer Vision

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.

Delivery, Consulting & Collaboration

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.

MLOps, Cloud & Responsible AI

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.

Required Qualifications

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.

Preferred Qualifications

Master's degree.

Healthcare experience.

Additional Information

You will report to a Lead Data Scientist.

Location & Work Style

This role is open to a remote work style in the U.S.

Eastern or Central time zone is preferred.

Ability to travel for on‑site team meetings (occasionally) on the East Coast.

Scheduled Weekly Hours: 40

The compensation range below reflects a good faith estimate of starting base pay for full‑time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job‑related skills, knowledge, experience, education, certifications, etc.

$97,900 - $133,500 per year

This job is eligible for a bonus incentive plan. This incentive opportunity is based upon company and/or individual performance.

Application Deadline: 05-07-2026

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section 503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements. This policy shall apply to all employment actions, including but not limited to recruitment, hiring, upgrading, promotion, transfer, demotion, layoff, recall, termination, rates of pay or other forms of compensation and selection for training, including apprenticeship, at all levels of employment.

Centerwell, a wholly owned subsidiary of Humana, complies with all applicable federal civil rights laws and does not discriminate on the basis of race, color, national origin, age, disability, sex, sexual orientation, gender identity or religion. We also provide free language interpreter services. See our full accessibility rights information and language options https://www.partnersinprimarycare.com/accessibility-resources

#J-18808-Ljbffr