Operations Analytics Lead

Group 1001

2d•$130,000 - $160,000•Remote

About The Position

Group 1001 is a consumer-centric, technology-driven family of insurance companies on a mission to deliver outstanding value and operational performance by combining financial strength and stability with deep insurance expertise and a can-do culture. Group1001’s culture emphasizes the importance of collaboration, communication, core business focus, risk management, and striving for outcomes. This goal extends to how we hire and onboard our most valuable assets – our employees. Why This Role Matters: The hardest problem in operations data isn't producing the insight; it's the last mile: the gap between an insight existing and the operation acting on it. That gap closes only when someone inside operations owns the problem and the outcome, not just the analysis. This is that person. You bring the operational fluency, the relationships, and the judgment to turn data and AI capability into changes that show up in how the contact center and back-office run, while a central data and engineering team handles the build. You frame the problem and own whether it lands; they own production. Both names on the work, never thrown over a wall.

Requirements

8+ years in a data product owner, analytics, or data-SME role, with a track record of data work that changed a business outcome, not just reports delivered.
Real fluency with operational data and reporting; you can read a messy data landscape and say what matters.
Analytical judgment: you can interrogate data and models critically and interpret them soundly without needing to build them yourself.
Comfortable partnering with a central data organization without turf friction; ideally, you’ve sat as the embedded data owner next to a central data team before.
Communication and influence: you turn analysis into decisions, earn the trust of senior stakeholders, and can hold a point of view, including an unpopular one.
Applied AI fluency: conversant in what AI and agentic capability can and can't do, and where it’s worth applying.
Working knowledge of the modern data stack (Snowflake and the tooling around it) so you can speak the builders' language.
Intellectual curiosity: you ask why the data looks the way it does, dig into discrepancies, and keep learning.
How you work with people matters as much as what you know: empathy and the instinct to read the room; you give feedback as a question and take it without ego; you stay flexible when plans shift, because they always

Nice To Haves

Insurance, financial services, or other regulated-industry background
Contact center or operations domain experience (Amazon Connect, Snowflake-based analytics
Hands-on experience defining dashboards or data products that teams use

Responsibilities

Translate the operations strategy into a prioritized set of the problems most worth solving with data, analytics, and AI. Separate a structural opportunity from quick win noise and own the call on what's worth doing.
Turn data into a narrative that changes a specific decision. Be the point of insight operations leadership turns to and hold your ground when the data contradicts the plan.
Drive insight into the real workflow and the moment of decision; you own whether it gets adopted, not just whether it gets delivered.
Qualify what's worth putting into the build queue, write the specs that make a hand-off succeed (clear definitions, the rules a shared data dependency must hold, and what “done" means), and judge whether what comes back is right.
As more of the work involves AI, help shape and qualify where it’s worth applying, and represent operations in how those capabilities get used and governed.