IT Business Analyst – Intelligence & AI

Northmarq•Minneapolis, MN

15h•Hybrid

About The Position

Northmarq is seeking a highly motivated Business Analyst to join their IT Automation & Intelligence team. The primary focus will be writing agile stories for the Data Engineering and AI teams, with a growing emphasis on AI-enabled solutions, agentic workflows, and intelligent automation. The ideal candidate will have a strong understanding of data, agile methodologies, business requirements gathering, and a working familiarity with modern AI tools (LLMs, copilots, and agent platforms). This role supports a flexible schedule that prioritizes in-office teamwork, with flexibility for remote work when appropriate.

Requirements

Bachelor's degree in Business, Information Technology, Data Science, or related field.
Minimum 3 years of experience in business analysis or related field – data science, machine learning, AI or adjacent experience a plus.
Strong understanding of data and data management principles.
Experience with agile methodologies and writing agile stories.
Working knowledge of AI concepts — large language models, prompts, retrieval-augmented generation (RAG), agents, and the difference between deterministic and probabilistic systems.
Hands-on experience using AI assistants (Microsoft Copilot, ChatGPT, Claude, or similar) in a professional context — bonus for experience writing requirements for AI/ML features.
Strong communication and interpersonal skills, with the ability to translate between business stakeholders and technical/AI teams.
Ability to work independently and manage multiple priorities in a fast-paced environment.
Strong analytical and problem-solving skills, with curiosity about how AI can reshape data workflows.

Nice To Haves

Experience writing acceptance criteria or evaluation rubrics for AI/ML features.
Familiarity with prompt engineering, agent design, or low-code automation (Power Automate, Power Apps, Copilot Studio).
Exposure to AI governance, responsible AI, or data privacy frameworks.

Responsibilities

Work with business stakeholders to identify data and AI use-case requirements, including opportunities to apply generative AI, machine learning, and intelligent automation.
Translate business requirements into agile stories for the Data Engineering and AI/Automation teams — including stories for AI features, prompt design, evaluation criteria, and human-in-the-loop workflows.
Partner with engineering teams to ensure stories are understood and that AI/data solutions are built with appropriate guardrails (accuracy, bias, privacy, explainability).
Define acceptance criteria for AI-driven features, including success metrics, evaluation datasets, and fallback behaviors when models are uncertain.
Participate in agile ceremonies (stand-ups, sprint planning, retrospectives) and AI design reviews.
Communicate with stakeholders to ensure delivered solutions — including AI copilots and automations — meet their needs and drive measurable outcomes.
Work with Quality Assurance to ensure stories are tested, including evaluation of AI outputs for accuracy, consistency, and safety.
Use AI tools (e.g., Microsoft Copilot, ChatGPT, internal agents) to accelerate your own work — drafting stories, summarizing stakeholder interviews, analyzing data, and prototyping requirements.
Identify and champion opportunities to embed AI into existing business processes and data products.
Stay current with industry trends in data, AI, agentic systems, and agile delivery practices.