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In support of Workato’s broader push toward becoming a wall‑to‑wall agentic company, one important area where this comes to life is the team’s investment in internal, agent‑powered systems, such as a User Insight Agent (PM Agent) that helps centralize feedback and package it into decision‑ready outputs. You’ll contribute to and benefit from that ecosystem, but the core of the role is broader: building a repeatable, modern “Insight Engine” for Product Research—powered by strong analytics, LLMs, and pragmatic automation—so insights land and drive measurable impact. Product Research needs a next‑gen Product Analyst who can: Synthesize qual + quant across product verticals to inform product and design decisions; Go beyond “insight generation” to also improve insight transmission, making insights easier to consume (briefs, artifacts, decision narratives) and more likely to be acted on; Build automations and agents that increase the day‑to‑day efficiency of the Research and Design team, so the team can move faster without sacrificing rigor.
Job Responsibility:
Multimodal analysis for product & design decisions (quant + qual): Work with qualitative and quantitative data sources to consolidate product signals across channels
Partner closely with Product Researchers, Designers, and Product Managers to define schemas and pipelines that make qualitative and quantitative signals joinable
Run analyses that inform product and design decisions: trend analysis, segmentation, lightweight experimentation readouts, measurement strategy, and narrative synthesis
Use LLMs to help turn messy qualitative data into structured, explainable representations
Build small tools/dashboards that keep decisions data‑informed
Help teams frame hypotheses, interpret results, and connect insights to product/design actions across Workato’s product offerings
Agentic insight delivery (insights that actually land): Build and iterate on a User Insight Agent that supports everyday product decisions
Create stakeholder‑ready outputs with traceable evidence, tailored to the decision being made
Design for trust and reliability: transparency, citations to source evidence, confidence/uncertainty signals, rigorous evaluation/guardrails, and human‑in‑the‑loop controls
Implement evaluation + observability so the system improves over time
Research & design team automations (increase team velocity): Create automations/agents that streamline daily operations for Research and Design, aiming to make the team faster and more effective across recruiting, study operations, synthesis workflows, and knowledge management
Treat internal ops as a product: measure time saved, throughput gains, and quality improvements
Alpha-test the Workato Agentic platform and Enterprise MCP capabilities and provide concrete feedback to Product/Design
Requirements:
Strong AI use encouraged: you’re excited to use AI tools to move faster (while staying rigorous about correctness, privacy, and safety)
Modern analytics skillset: strong SQL + data wrangling
comfortable translating messy questions into clean analysis
Text/qual comfort: excited to analyze and structure qualitative data (transcripts, notes, open‑ended feedback) alongside quantitative signals
LLM + agentic systems fundamentals: familiarity with prompting, structured outputs, tool/function calling, retrieval/RAG, and basic evaluation/guardrails
Product sense: you can clearly articulate tradeoffs, propose practical workflows, and align outputs to stakeholder decisions
Clear communication: you can make complex findings and systems legible through crisp writing, visualizations, docs, and demos
Graduating senior with a relevant BS/MS degree (CS, Data Science, HCI, Design Engineering, or related)
Junior candidates with <2 years of experience and strong relevant projects may also be considered
Nice to have:
Familiarity with MCP (Model Context Protocol) or agent frameworks
observability/eval tooling for LLM systems
Experience joining qualitative research artifacts with product telemetry in a principled way
Background in experiment design, causal thinking, or measurement strategy
Experience working in a SaaS environment or with enterprise customers
Ability to build lightweight UIs (e.g., TypeScript/React) for internal tools
Reliability mindset (testing, monitoring, safe iteration) for data/LLM workflows
What we offer:
A front‑row seat and real ownership on what “next‑gen analytics” looks like in an agentic company
Mentorship across Product Research, Design, PM, Engineering, and AI Lab teams
The chance to ship state-of-the-art Agentic products—both internally, and externally to customers—that influence real product decisions and help shape how insights flow through the org
Hands‑on experience building, evaluating, and hardening LLM/agent workflows for real stakeholders and real decisions
A stronger portfolio of practical work artifacts (insight narratives, lightweight tools, automations, evaluation setups) you can talk about
A flexible, trust-oriented culture
A vibrant and dynamic work environment
A multitude of benefits they can enjoy inside and outside of their work lives