Data Scientist - Fun.xyz

deCircle

New York (NY)

On-site

USD 100,000 - 130,000

Full time

14 days+

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Job summary

A blockchain technology company is seeking a Data Scientist to enhance their data-driven strategy. This role involves designing scalable data models, optimizing data transformations, and providing insights into business performance. Candidates should have over 5 years of experience with Python and SQL, backed by a strong foundation in statistical analysis. An interest in crypto and DeFi is essential. The position is well-suited for fast-paced environments that value ownership and problem-solving.

Qualifications

  • 5+ years of experience in Python and SQL.
  • Strong background in statistical analysis and experimentation.
  • Experience with data platforms and orchestration tools.

Responsibilities

  • Design and build scalable data models.
  • Support optimization of data transformations.
  • Provide insights on business performance.
  • Maintain data quality across analytical systems.
  • Deliver actionable insights with product teams.
  • Run experiments and drive product decisions.
  • Translate complex data into clear stories.

Skills

Proficiency in Python
Proficiency in SQL
Statistical analysis
Experimentation and causal inference
Analyzing end-user behavior
Working knowledge of data platforms
Interest in crypto and DeFi

Tools

Redshift
Snowflake
Databricks
dbt

Job description

Fun.xyz

At Fun.xyz, we believe a tokenized future is a beneficial inevitability, granting financial emancipation to everyone with an internet connection. For a blockchain-first global economy to exist, value exchange must become intuitive, secure, and seamless.

Enter Checkout — the highest converting payment solution in web3. By integrating Checkout, dApps enable users to complete any on-chain action using crypto from a wallet, centralized exchange, or on-ramped fiat from a card or bank account. With access to market-leading routing and their asset portfolio at the point of sale, users are faster, stickier, and more engaged. For dApps, Checkout scales their user acquisition potential without launching new chains or integrating multiple third party providers.

We built Checkout because we envision a world where anyone, anywhere, can purchase anything with any asset. If that sounds like a vision you can get behind, we want to hear from you.

Role Overview

We’re looking for a Data Scientist to supercharge our data-driven strategy and ensure we’re building the right things at the right time. You’ll be embedded in the heart of our product and engineering teams, shaping insights that guide strategy, uncover user behavior, and optimize execution across Fun.xyz.

This role is perfect for someone who thrives in fast-paced, ownership-driven environments, loves solving open-ended problems, and is excited about the potential of blockchain data.

Responsibilities
  • Design and build scalable data models to analyze transaction flows and user behavior
  • Support the optimization of data transformations, pipelines, and workflows
  • Work directly with the CFO to provide insights on the business’ performance
  • Maintain data quality, observability, and reproducibility across analytical systems
  • Partner with engineers and product teams to deliver actionable, production-grade insights
  • Run experiments, apply causal inference, and drive evidence-based product decisions
  • Translate complex data into clear stories for both technical and non-technical stakeholders
Qualifications
  • Proficiency in Python and SQL (5+ years)
  • Strong background in statistical analysis, experimentation, and causal inference
  • Familiar with analyzing end-user behavior for optimization (A/B testing, conversion rates, etc.)
  • Skilled in modern data platforms (Redshift, Snowflake, Databricks, etc.) and orchestration/transformation tools (dbt or similar)
  • Deep curiosity about crypto, DeFi, on-chain data, and Web3 infrastructure
Nice to Have
  • Experience analyzing large-scale transaction or financial datasets
  • Hands-on experience with ML/AI libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow)
  • Familiarity with market dynamics (spreads, slippage, liquidity, etc.)
  • A track record of thriving in ownership-heavy, fast-moving environments
  • A problem-solving approach that blends rigor, creativity, and first-principles thinking
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