Fully remote. US-based preferred. If international, significant overlap with US working hours is required.

About TYB

TYB is an AI-powered community commerce platform connecting brands with their most passionate fans through challenges, rewards, and social features. We're Series A and moving fast across a dual-sided marketplace that serves both consumers and brand partners.

The role

We're hiring a Data Analyst to turn TYB's product and business data into decisions. This is a hybrid analyst / analytics engineer role: most of your time will go toward analysis, dashboards, and experimentation, but you'll also build and maintain the dbt models in our Redshift warehouse that those analyses depend on.

You'll be the connective tissue between data and the rest of the company. You'll work closely with product, engineering, customer success, and our data science team to define how we measure success, design and run experiments, and make sure everyone is working from the same trusted numbers across both sides of our marketplace.

You'll have real ownership in a 0-1 environment where the process is still being built, and direct influence over which metrics the company tracks and how it learns from its experiments.

We build with AI, and we expect you to as well — using AI to move faster in your own workflow (writing SQL, exploring data, drafting analyses, documentation) and thinking about where AI-assisted tooling can make self-serve analytics easier for the rest of the team.

What you'll do

• Build and maintain dashboards in Hex and Amplitude covering consumer behavior, app performance, brand partner outcomes, and key business metrics
• Independently field ad-hoc analysis requests from teams across the company, scoping the real question and delivering clear, decision-ready answers
• Design, launch, and analyze A/B tests and feature experiments, including hypothesis design, sample size and power estimates, guardrail metrics, and readouts with recommendations
• Run survey work and other statistical analyses of customer behavior, such as funnels, cohorts, retention, and engagement
• Build and maintain dbt models in Redshift that turn raw product and event data into clean, tested, documented tables for analysis
• Define and document core metrics so the whole company works from one consistent set of definitions
• Partner with engineering and product on event tracking in Amplitude, making sure new features ship with the instrumentation needed to measure them
• Work with engineering, product, and customer success to build an end-to-end understanding of the product, so analytics reflects how TYB actually works
• Meet regularly with the data science team to plan and review analytics strategy against current business needs
• Enable self-serve analytics by making data easy to find, understand, and trust for non-technical teammates

What we're looking for

• 5+ years of experience as a data analyst, product analyst, or analytics engineer, ideally at a consumer app or marketplace company
• Advanced SQL skills and hands-on experience with a cloud data warehouse (Redshift or equivalent, e.g., Snowflake, BigQuery, Databricks)
• Experience building and maintaining data models in dbt, including tests and documentation
• Solid grounding in statistics and experiment design: hypothesis testing, statistical significance and power, and common pitfalls like peeking and novelty effects
• Experience running A/B tests end-to-end, ideally with a feature flagging or experimentation platform such as LaunchDarkly, Statsig, Optimizely, or Amplitude Experiment
• Experience with product analytics tools such as Amplitude or Mixpanel, and with BI or notebook tools such as Hex, Mode, or Looker
• Working proficiency in Python for analysis
• Comfortable in a 0-1 environment: scrappy, self-sufficient, and able to prioritize competing requests without a large data team around you
• Strong communicator who can translate analysis into clear recommendations for product, engineering, and business stakeholders

Nice to have

• Hands-on experience with LaunchDarkly experimentation specifically
• Experience designing event tracking plans or taxonomies for a product analytics tool
• Familiarity with experimentation methods such as sequential testing, and holdout groups
• Experience with e-commerce, loyalty, creator, or community products, or with analytics for two-sided marketplaces
• Experience building a metrics or semantic layer
• Experience applying LLMs to analytics workflows, such as AI-assisted querying or automated reporting
• Early-stage startup experience

What we offer

• Remote work, with optional offices in San Francisco
• Competitive salary
• Flexible time off
• Work environment where you can be involved in shaping the product early on, own its development end-to-end, with freedom and flexibility to figure things out as you go