Product Analyst – AI

NISC develops and implements enterprise-level and customer-facing software solutions for over 960+ energy cooperatives and communication organizations across North America. Our mission is to deliver technology solutions and services that are Member-focused, quality-driven and valued-priced. We exist to serve our Members and help them serve their communities through our innovative software products, services and outstanding customer support. We are an AI-forward company committed to being a technology leader in our industry.

NISC has been ranked in Computer World’s Best Places to Work for 23 years, and we are looking for qualified individuals to join our team.

Summary:

We’re building the next generation of intelligent tools that empower NISC Members and their communities. As a Product Analyst – AI, you’ll play a key role in shaping how AI insights, automation, and predictive capabilities are integrated into NISC’s enterprise software ecosystem — from our customer-facing AI Assistant to our intelligent operations tools, reporting, and data-driven decision support systems.

You’ll bridge product design, analytics, and data science to ensure every AI-powered feature we deliver is useful, explainable, and aligned with Member needs.

Work Schedule:

• Hybrid from one of our three office locations:
  • Cedar Rapids, IA
  • Lake Saint Louis, MO
  • Mandan, ND
• Hybrid
  
  Schedule:
  
  Minimum of working 3 days per week in the office and ability to work up to all 5 days a week in the office, as needed
• Required Days from an Office
  
  Location:
  
  Tuesday and Wednesday - the third required day will be up to the candidate and their supervisor to choose
• Partner with Product Management, Design, and Engineering to define data-informed requirements for new AI and intelligent features.
• Write user stories, define acceptance criteria, and translate model outputs into meaningful user experiences.
• Define and maintain key product health metrics — usage, adoption, retention, and ROI — for AI features and products.
• Conduct deep-dive analyses into user interactions with AI tools (e.g., prompt quality, model relevance, workflow outcomes).
• Collaborate with data scientists and ML engineers to evaluate and monitor model performance, including accuracy, drift, fairness, and edge cases.
• Build dashboards and monitoring systems that track AI system health and highlight actionable insights.
• Perform exploratory data analysis and partner with Product Management teams to identify opportunities for automation, prediction, and decision support across NISC products.
• Benchmark industry AI trends and third-party tools to help shape product direction.
• Partner with internal enablement and support teams to promote understanding of NISC’s AI tools, roadmaps, and ethical design principles.
• Clearly communicate insights and recommendations to technical and non-technical audiences, ensuring alignment with NISC’s mission and Member values.
• Maintain documentation of analytical approaches, ensuring transparency, reproducibility, and explainability in all work.
• Stay informed on AI governance, compliance, and responsible AI practices, helping NISC maintain a “human-in-the-loop” approach across all AI solutions.
• Other related duties as assigned.
• Commitment to NISC’s Statement of Shared Values.

Knowledge, Skills & Abilities Preferred:

• 3+ years of experience in product analytics, data analytics, or BI — ideally with exposure to AI, ML, or predictive product features.
• Excellent analytical and communication skills — able to translate technical findings into clear, Member-focused recommendations.
• Comfortable working cross-functionally and iteratively in a fast-moving, data-informed environment.
• Passion for responsible, transparent, and explainable AI that improves human work rather than replaces it.
• Strong understanding of machine learning fundamentals — model evaluation, feature importance, overfitting, and drift.
• Experience interpreting model outputs (e.g., predictions, classifications, probabilities) and turning them into actionable product insights.
• Proficiency in SQL and one or more data visualization tools (Tableau, Power BI, Looker, or Quick Sight).
• Familiarity with cloud data platforms (AWS, GCP, or Azure)…