Data Scientist – Generative AI, Agentic AI, NLP & LLMs

About the role

Location: Chicago, Illinois. Work location: 433 W Van Buren St, Suite 805, Chicago, IL 60607. Duration: 6 months. Start date: November 1, 2026. Contract duration: 24 months.

Responsibilities

• Design and implement advanced machine learning, generative AI, and agentic AI solutions using structured and unstructured data.
• Build and deploy scalable, automated data science products and reusable analytical assets.
• Design agentic AI architectures integrating LLMs, retrieval systems, structured data, APIs, tools, business rules, routing logic, and approval checkpoints.
• Optimize RAG solutions to improve retrieval quality, accuracy, and response reliability.
• Develop AI evaluation frameworks to measure accuracy, reliability, hallucination risk, latency, cost, safety, and consistency.
• Collaborate with engineering, platform, business, and client teams to deploy production-ready AI solutions.
• Monitor, maintain, and improve deployed AI models and applications.
• Ensure responsible AI practices, governance, validation, explainability, and risk management.
• Communicate technical findings and AI solution outcomes to business and technical stakeholders.
• Lead complex analytics and AI initiatives.
• Provide technical guidance and mentorship to data scientists.
• Conduct code reviews and promote coding best practices.
• Make analytical and architectural decisions.
• Establish technical standards and reusable frameworks.
• Communicate complex analytical findings to technical and non-technical audiences.
• Collaborate with stakeholders and clients on strategic, operational, and clinical objectives.

Requirements

• 7+ years of relevant experience in data science, analytics, machine learning, or AI (6‑8 years listed in role requirements).

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent experience.

Skills

• Expertise in statistical modeling, machine learning, generative AI, agentic AI, and Natural Language Processing (NLP).
• Strong knowledge of Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), autonomous decision‑making frameworks, and human‑in‑the‑loop workflows.
• Proficiency in Python, R, SQL, SAS, or similar analytical programming languages.
• Experience with Databricks, cloud‑based platforms, and distributed computing.
• Hands‑on experience with vector databases, semantic search, knowledge graphs, metadata management, and enterprise search.
• Experience deploying, monitoring, and maintaining production AI solutions.
• Knowledge of Responsible AI, model governance, explainability, bias detection, hallucination evaluation, and risk controls.
• Desirable: Cloud‑based AI platforms, Databricks and distributed computing, vector databases and semantic search, knowledge graphs and enterprise search, AI governance and model monitoring.