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