Product Analyst

Wand

• $100K — $120K *
US-Anywhere
+ 2 other locationsRemote
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in Data Analyst, Product Analyst, or Business Intelligence roles (not including internships)
  • Proficient in SQL with capabilities for complex queries and optimizations
  • Experience using Python for data analysis
  • Knowledgeable in experimentation methods including hypothesis testing and sample size determination
  • Demonstrated success in improving key metrics and decision-making outcomes
  • Ability to communicate tough insights clearly and directly to leadership

Responsibilities

  • Own and maintain critical business metrics and dashboard definitions
  • Conduct thorough investigations into performance anomalies and provide actionable insights
  • Design, execute, and analyze A/B tests for product enhancements
  • Collaborate with leadership to tackle complex analytical questions
  • Provide data-driven recommendations to enhance product strategy

Benefits

  • Fully remote work environment with flexible hours
  • Emphasis on efficient communication and minimal meetings
  • Opportunity to engage in gaming as part of the culture
  • Fast-paced shipping of projects while documenting processes
  • Focus on strategic impact and measurable improvement in metrics
Full Job Description
About the Role

Wand is seeking a Product Analyst to own the metrics that matter most and chase down the questions nobody else has time for. You'll partner with Product, Growth, Marketing, and Finance - not as a service desk, but as a peer who pushes back when the question being asked isn't the right one.

You'll set the analytical bar, define the metrics frameworks the rest of the team relies on, and run the experiments that decide what ships. Data engineering owns the pipelines; you'll focus on the analysis, the recommendation, and the decision that follows.

What You'll Do
  • The metrics that decide what ships. You'll define what Product, Growth, Marketing, and Finance measure - and, more importantly, what each metric is there to help decide. You'll notice when we're tracking the wrong thing, and adjust the framework as the business evolves. You'll build in Hex, document in our spec, and enforce consistent definitions across teams.
  • Deep investigation. When retention dips or a funnel leaks, you won't stop at the symptom. You'll follow the thread - through cohorts, segments, the quirks of specific games - until you can name the cause and recommend a fix. You'll notice when a chart doesn't look right and you won't leave it alone.
  • Experimentation. You'll design and analyze A/B tests on product changes, pricing, onboarding, and growth initiatives. You'll set sample sizes, call stat sig, and write the readouts. When a result is noisy or a test is underpowered, you'll say so - even when the PM is ready to ship.
  • Strategic partnership. You'll work directly with our leaders on the questions that don't have obvious answers. What are players actually doing in Game Guide? Which customizations predict long-term retention? Why does Wand Pro convert better in some game categories than others? You'll frame the question, run the analysis, and deliver the recommendation.
What you'll be measured on
  • The decisions you unblocked. The metrics you improved. The bad ideas you killed before they shipped. The questions you answered before anyone thought to ask them.
Who You Are

Core requirements:
  • 5+ years as a Product Analyst on a consumer software or gaming team. Not a BI, reporting, or dashboarding role - this is a role about product decisions
  • Track record of translating an ambiguous product question into a decision that changed what shipped (we'll ask you to walk us through one)
  • SQL fluency - complex joins, incremental computation, window functions, query optimization; comfortable with large, messy datasets
  • Python for analysis - pandas and statistical libraries; you don't freeze when the answer requires code
  • Experimentation chops - hypothesis testing, sample sizing, and the judgment to tell a p-value from an insight
  • Direct communication - you can tell a leader an uncomfortable answer without burying it in caveats

Preferred qualifications:
  • Degree in a quantitative field
  • Hex, dbt, and BigQuery experience
  • Causal inference methods (diff-in-diff, regression discontinuity, propensity matching)
  • Prior work on LTV, retention, or subscription models
  • Experience building metrics frameworks or KPI hierarchies from scratch
What We Offer
  • Competitive compensation and equity package.
  • Fully remote work arrangement.
  • The chance to do unusually deep native work for an audience of 40M+ players who will actually feel the difference.
  • A team of people who genuinely love games, move incredibly fast, and care deeply about what they build.

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