Data Analyst
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Key skills for this role
About the Role
Senior Experimentation Analyst - Owning high-stakes tests end to end. Analytics Engineer - Building the data layer and self-serve tooling the whole team relies on. What takes 4-.
Key Skills for This Role
Responsibilities
- Analyze A/B tests end to end and deliver decision ready recommendations
- Map user journeys across devices and traffic sources to identify friction and conversion leaks
- Build and maintain data pipelines across Shopify, GA4, Google Ads, and BigQuery
- Contribute to a structured hypothesis pipeline and define success criteria
- Orchestrate agentic AI workflows to accelerate analysis using SQL and Python
- Collaborate with marketing, UX, and development to translate findings into site changes
Requirements
- Strong SQL and Python skills
- Experience with A/B testing and experimentation
- Ability to build and maintain data pipelines
- Experience with analytics engineering and self serve tooling
- Familiarity with Shopify, GA4, Google Ads, BigQuery
Full Job Posting
Role Overview
- Senior Experimentation Analyst Owning high stakes tests end to end.
- Analytics Engineer Building the data layer and self serve tooling the whole team relies on.
- What takes 4 5 years elsewhere happens in 1 2 here.
Who You'll Work With
- You'll sit within the Analytics team and collaborate closely across the organization.
- Senior Management: Your recommendations shape site and campaign decisions.
- Digital Marketing Team: Tie ad platform data to on site behavior across the full funnel.
- CRO: Partner on hypothesis prioritization and test design.
- Dev & QA: Translate winning tests into production and validate implementation.
- Finance: Connect experimentation outcomes to revenue impact.
- Customer Support: Surface post purchase friction that feeds upstream test ideas.
- Our team includes alumni from Apple, Deutsche Bank to name a few.
What You'll Own
- Analyze A/B tests end to end: what worked, what didn't, why and deliver decision ready recommendations, not metrics readouts.
- Map user journeys across devices and traffic sources; pinpoint friction, drop offs, and conversion leaks; convert them into prioritized, testable hypotheses.
- Dig into data at segment, device, source, and journey step level to find the non obvious drivers that top line reporting misses.
- Build and maintain your own data pipelines across Shopify, GA4, Google Ads, and BigQuery: you don't wait in a queue to get the data you need.
- Contribute to a structured hypothesis pipeline: prioritize by impact, write clear test briefs, define success criteria upfront, and push proposals to execution.
- Orchestrate agentic AI workflows to accelerate analysis using SQL and Python as the foundation to direct, validate, and scale your analytical output.
- Collaborate with marketing, UX, and development to translate findings into site changes, campaign adjustments, and creative decisions.
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