Senior Data Scientist

Phantom is on a mission to connect the world to the freedom of open markets. Tens of millions of people all over the world use Phantom to access global markets that never close, including perpetuals, prediction markets, tokenized assets, stablecoins and memes. Phantom users are able to discover the markets that matter and the cultural moments that shape them, building conviction through real-time data and the verified performance of top traders. With self-custody and access to open networks at its core, Phantom lets them control their financial moves in the same app they use to safely store or spend money worldwide.

Phantom has reached #1 in Google Play's finance category and consistently ranks in the top 50 apps across all categories. Check out our Forbes Fintech 50 and CNBC and Statista's World's Top Fintech Companies 2026!

We are around 180 people, fully remote, backed by a $150M Series C investment from a16z, Sequoia Capital and Paradigm.

As a Data Scientist at Phantom, you’ll help shape our consumer products through rigorous analysis, experimentation, and reliable data. You’ll work closely with Product, Engineering, Design, and Growth to understand user behavior, identify opportunities, and guide product decisions.

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  Analyze user journeys, activation, engagement, retention, and monetization to identify opportunities and recommend product improvements.

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  Design and evaluate A/B tests, including hypotheses, success metrics, guardrails, sample sizing, and interpretation. Communicate uncertainty and distinguish observed relationships from causal effects.

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  Define and maintain product metrics, and partner with Engineering to improve instrumentation and validate the data behind them.

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  Build reusable analytical datasets and dbt models using SQL. Collaborate with Data Engineering on Snowflake, Dagster, and ETL pipelines to improve data quality and support analysis.

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  Use Python for statistical analysis, modeling, and automation. Make your work reproducible, documented, and maintainable.

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  Incorporate AI coding tools such as Codex, Claude Code, and Cursor into your workflow to accelerate development and analysis. Review and validate generated code, assumptions, and results.

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  Independently lead ambiguous problems from initial question through analysis, recommendation, and measurement. Communicate clearly, challenge assumptions constructively, and influence priorities across teams.

• 7+ years of experience in data science, product analytics, or a related field, with a demonstrated record of influencing product decisions.

• Strong foundation in statistics, including probability, statistical inference, hypothesis testing, regression, and sources of bias and confounding. Ability to select appropriate methods and explain their assumptions and limitations.

• Practical experience designing and analyzing A/B tests, including defining metrics, assessing statistical power, checking experiment validity, and translating results into decisions.

• Advanced SQL skills and strong proficiency in Python for data exploration, statistical analysis, and reproducible analytical workflows.

• Working knowledge of dbt, data modeling, and modern data platforms. Familiarity with orchestration tools such as Dagster and how ETL pipelines, dependencies, and refresh schedules affect downstream analysis.

• Hands-on experience using AI coding tools such as Codex, Claude Code, or Cursor in your regular workflow, with the judgment to verify correctness and maintain code quality.

• Experience partnering directly with product teams, ideally on consumer products, to understand behavior and improve activation, engagement, retention, or monetization.

• Ability to independently structure ambiguous problems, prioritize work, and communicate recommendations to technical and nontechnical partners.

• Curiosity, initiative, and a willingness to learn unfamiliar systems and follow through on useful work.
  

• Experience working with Snowflake, including querying large datasets and understanding query performance and cost.

• Experience with crypto, tokenized assets, finance, or fintech.