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

Job Description: Data Scientist – Generative AI, Agentic AI, NLP & LLMs

Job Details

• Job Title: Data Scientist – Generative AI / Agentic AI / NLP / LLMs
• 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 Mentioned: 24 months
• Experience Required: 7+ years (6–8 years listed in role requirements)
• Base Salary Range: $118K (minimum and maximum range not specified)
• Education: Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent experience.

Must-Have Technical/Functional Skills

• 7+ years of relevant experience in data science, analytics, machine learning, or AI.
• 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.

Roles and 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.

Generic Managerial Skills

• 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.

Keywords to Search in Resumes

• Core Roles: AI Engineer, Data Scientist, Machine Learning Engineer, Data Science, Statistical Modeling.
• AI and ML: Machine Learning (ML), Generative AI, Agentic AI, Natural Language Processing (NLP), Large Language Models (LLMs).
• LLM Technologies: Prompt Engineering, Retrieval-Augmented Generation (RAG), Autonomous Decision-Making, Human-in-the-Loop.
• Programming and Platforms: Python, R, SQL, SAS, Databricks, Distributed Computing, Cloud Data Platforms.
• Search and Data Technologies: Vector Databases, Semantic Search, Knowledge Graphs, Metadata Management, Enterprise Search.
• Responsible AI: Model Governance, Explainability, Bias Detection, Hallucination Evaluation, Model Validation, Production AI Monitoring.

Pre-Screening Questionnaire

• Do you have 7 or more years of relevant experience in data science, analytics, machine learning, or AI?
• Describe your hands-on experience with machine learning, generative AI, agentic AI, NLP, LLMs, prompt engineering, and RAG.
• Have you designed agentic workflows using retrieval systems, APIs, tools, business rules, routing logic, escalations, and human approval checkpoints?
• Which programming languages and platforms have you used, including Python, R, SQL, SAS, Databricks, cloud, or distributed computing platforms?
• Have you deployed and monitored production AI solutions?
• Do you have experience with Responsible AI, model governance, explainability, bias detection, validation, and risk controls?

Role Description

• Data Scientist specializing in Generative AI, Agentic AI, Natural Language Processing (NLP), Large Language Models (LLMs), Data Science, and Machine Learning (ML).

Essential Skills

• Data Science
• Generative AI
• Agentic AI
• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Machine Learning (ML)

Desirable Skills

• Cloud-based AI platforms
• Databricks and distributed computing
• Vector databases and semantic search
• Knowledge graphs and enterprise search
• AI governance and model monitoring

Skills Classification

• Digital: Data Science
• Digital: Natural Language Processing (NLP)
• AI & Generative AI: Products and Tools