Data Analytics Specialist
at G2
Chicago, IL; Remote (US), remote, mid, full time, USD 1,30,000–1,50,000 / year, 4–6 years
posted 01 Jul 2026
- R
- Power BI
- Sigma
- AI agents
- A/B testing
- Tableau
- Looker
- LLM tooling
- SQL
- Python
About the role
The Product Data Science team is G2's centralized analytics and data science function, embedded within the Product org to support Product Leadership and the teams building our buyer experience and reviews platform. In this role, you'll partner closely with product stakeholders to develop data-driven strategies that improve the product and deliver measurable outcomes. You'll also drive self-service initiatives, giving end users direct access to insights through dashboards and MCP-powered tooling. Day-to-day, you'll work across a modern data stack including Looker, Snowflake, Amplitude, Python, and R, applying experimentation frameworks and data storytelling techniques to turn complex analysis into clear, actionable recommendations.
What you would do
As a member of the Product Data Science team, your responsibilities will include a variety of business intelligence, data analysis and ad-hoc queries, such as -
- Partner with product leaders and PMs to set and drive OKR goals for your domain, owning the core metrics and the data-led initiatives that move them
- Lead end-to-end implementation of analytics projects for your domain, from scoping and instrumentation through delivery and adoption
- Design and build analytics products that generate actionable insights for both internal stakeholders and external customers
- Build automation workflows, AI agents, and MCP-powered tooling that enable teams across the organization to self-serve data
- Mentor analysts on the team and raise the bar on agentic workflows and analytics product development
- Define and improve data quality, documentation, and governance standards to ensure the data layer is accurate, trusted, and AI-ready
- Lead exploratory and ad-hoc analyses for product and leadership partners, synthesizing complex data into clear, decision-ready recommendations
- Build and maintain BI infrastructure in Looker and Amplitude, including dashboards, explores, and self-service reporting layers
- Partner with data science, AI engineering, AI research, and product to define data requirements for experimentation
- Act as a data thought partner to product teams, proactively surfacing insights, flagging risks, and shaping strategy through a data lens
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