Associate Data Scientist 2027

About the Role

IBM's Associate Program is designed for university hires ready to kick-start their careers by collaborating with global clients and IBM teams on projects involving digital transformation, cloud strategy, AI adoption, process redesign, analytics, generative AI, and agentic AI-enabled transformation. As an Associate, you will work with a diverse cohort of peers, gain access to industry-recognized certifications, digital badges, and structured learning on IBM's AI-driven learning platform. The role is suited for analytical problem solvers who want to use data science, machine learning, and GenAI/Agentic AI-enabled workflows responsibly.

Your Role and Responsibilities

As an Associate Data Scientist, you will contribute to generative AI and agentic AI workflows, utilizing open-source tools such as Python, R, and TensorFlow, alongside IBM tools and AI application suites.

• Prepare, analyze, and understand data to deliver insight, predict emerging trends, and evaluate model and workflow performance.
• Collaborate closely with diverse teams to select appropriate modeling approaches and identify critical data needs.
• Translate complex model results into clear recommendations for technical and non-technical audiences.

In Your Role, You May Be Responsible For

• Prepare, cleanse, join, and analyze structured, semi-structured, and unstructured data for analytics, machine learning, GenAI, and agentic AI workflows.
• Implement and validate predictive, prescriptive, statistical, and machine learning models with a focus on measurable client and business outcomes.
• Design experiments, features, prompts, evaluation datasets, metrics, and tests to assess model outputs, workflow accuracy, reliability, bias, and business value.
• Build GenAI, RAG, and agentic AI workflows by evaluating retrieval quality, grounding, generated responses, tool-use outcomes, and end-to-end agent performance.
• Work in an Agile, collaborative environment with data scientists, data engineers, AI engineers, consultants, architects, and database administrators to bring analytical rigor and responsible AI practices to client challenges.
• Communicate with internal and external clients to understand business needs, select appropriate modeling techniques, and explain assumptions, limitations, and recommendations.
• Evaluate modeling results and present insights clearly to technical and non-technical audiences, translating findings into practical actions.

These positions are anticipated to start in 2027.

Locations: Chicago

Requirements & Tech Stack

• Strong fundamentals in mathematics, statistics, computer science, algorithms, and analytical reasoning.
• Familiarity with programming languages such as Python, SQL, R, or similar.
• Foundational understanding of predictive modeling, prescriptive modeling, statistical methods, machine learning, GenAI, and Agentic AI.
• Basic understanding of cloud environments, data platforms, or AI platforms such as AWS, Azure, Google Cloud, or similar.
• Strong technical and analytical abilities, problem-solving, debugging, troubleshooting, teamwork, and communication skills.
• Willingness to travel up to 100%, based on project requirements.

Preferred Technical And Professional Experience

• Coursework, projects, internship experience, or portfolio work involving data science, machine learning, analytics, GenAI, and Agentic AI.
• Familiarity with LLMs, embeddings, vector databases, retrieval systems, prompt workflows, RAG, model behavior evaluation, and AI agent workflow patterns.
• Exposure to orchestration and agentic AI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, MCP-based tooling, or similar tools.
• Understanding of Git, containers, APIs, testing frameworks, CI/CD, MLOps, LLMOps, observability, model monitoring, data governance, privacy, security, or responsible AI practices.
• Bachelor's degree in a related field such as Computer Science, Data Science, Statistics, Mathematics, MIS, Engineering, AI/ML, or another quantitative field.