Data Analyst

Own the experimentation engine behind a $1Billion+ e-commerce brand's growth decisions.

Total Annual Package: Up to USD $118,750 + comprehensive benefits (Base salary + monthly performance bonus of up to 25% of base)

Location: Remote (Global)

Growth path from here is: Senior Data Analyst → Analytics Engineer. Career progression that takes 4-5 years elsewhere can happen in 1-2 years here for high performers.

We've been AI-first since December 2023: You'll use agentic AI workflows to accelerate analysis and refine your analytical output. You remain accountable for validating the findings and turning them into clear business recommendations.

Role Overview:

Puffy, a market-leading, nine-figure D2C brand and Top 5 US mattress brand with over $1Billion in sales, is hiring a Data Analyst to own its experimentation program, covering test design, statistical analysis, funnel diagnosis and data pipelines, reporting directly to the Analytics Manager.

This role exists to turn raw customer and acquisition data into clear recommendations that Marketing, UX and Development can act on the same week.

The Problems You'll Own:

• Primary: Turn test results into growth decisions: Experiment results need to explain what worked, what did not and why across devices, traffic sources and customer-journey steps. The challenge is separating meaningful findings from noise and turning them into recommendations that Marketing, UX and Development can act on.

• Secondary: Connect the evidence without slowing decisions: The acquisition-to-conversion picture spans Shopify, GA4, Google Ads, Meta and BigQuery. Independent analysis depends on connected source data and validated outputs rather than pre-built dashboards alone. The challenge is keeping that evidence usable and reliable as analytical output scales.

The Career Accelerator:

This is not a role where you manage dashboards and pass the analysis to someone else.

• The scope is scarce: You'll work across test design, statistical analysis, funnel diagnosis and your own data pipelines, with direct access to the Analytics Manager. You pull the data yourself and remain accountable for the quality of your recommendations.

• Your first 12 months: Analyze A/B tests end to end, explaining what worked, what did not and why. Prioritize hypotheses by impact and define test briefs, success criteria and sample sizes upfront. Turn findings into site changes, campaign adjustments and creative decisions with Marketing, UX and Development. Map journeys across devices and traffic sources to identify friction and conversion leaks. Connect Google Ads and Meta data to the acquisition-to-conversion funnel. Use SQL and Python agai...

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