Data Science & GenAI Research Intern - IGEN

POSITION SUMMARY

Join the Insight Engineering team for Summer 2026, starting May 2026. This internship is dedicated to applied research and development in data science and Generative AI — with a particular focus on agentic systems that reason over enterprise data.

You will work alongside the foundation team that is standing up our Snowflake-anchored data platform, semantic layer, and KPI certification discipline. Your role is the R&D wedge: prototyping the AI capabilities that will eventually be embedded into IGEN products and shared as certified, governed insight with clients and partners.

This is not a ticket-queue internship. You will own experiments end to end — framing the question, building the prototype, evaluating it honestly, and writing up what you learned so the team can decide what to productize.

This internship will be located onsite at our Corporate Headquarters [222 W College Avenue, Appleton, WI 54911]. This intern will sit inside the Insight Engineering squad alongside the Sr. Data Engineer and BI Engineer, and will partner with product squads where R&D output intersects their roadmap.

JOB RESPONSIBILITIES

What You’ll Work On 

Project scope is set at the start of the internship based on team priorities and your strengths, but representative R&D tracks include: 

GenAI Agentic Systems 

• Prototype agents that answer business questions by reasoning over certified KPIs, semantic models, and operational data — not by guessing. 

• Build retrieval-augmented pipelines over structured warehouse data and unstructured documents (regulatory content, internal documentation, ticket history). 

• Explore tool-use patterns where an LLM orchestrates SQL generation, validation against the semantic layer, and result interpretation — with governance and lineage preserved. 

• Evaluate model behavior rigorously — accuracy, hallucination rates, latency, cost — and document trade-offs. 

Data Science & Applied ML 

• Develop and test models against governed datasets in Snowflake — forecasting, classification, anomaly detection, or entity resolution depending on the active research question. 

• Engineer features that could land in a future feature store, with attention to lineage, reproducibility, and certified inputs. 

• Run experiments using Snowflake Cortex AI (native LLM and ML functions in SQL), Python notebooks, and other appropriate tooling. 

Research Communication 

• Write up findings in a way the engineering team, product partners, and SLT can consume — what was tried, what worked, what didn’t, and what to do next. 

• Demo prototypes to the Insight Engineering team and contribute to the decision of whether a capability is ready to move from R&D into the platform roadmap. 

What You’ll Learn 

• How a real data platform gets built: ingest, normalization, semantic layer, certification, governance — not just the demo version. 

• How GenAI capabilities are evaluated and made production-credible in an enterprise context where hallucination is not an acceptable failure mode. 

• How insight engineering treats AI as a deliverable that must be owned, named, dated, and versioned — the same discipline as code. 

• How research output becomes product input: the path from prototype to roadmap to revenue. 

Why This Internship 

Most data internships ask you to fix dashboards or clean a backlog. This