Data Scientist - Fun.xyz
At a glance
Mid-level Data Science role at deCircle. New York · full-time · no salary stated · we estimate $137,581–$208,900.
deCircle has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build data models that reveal how transactions move and how users behave
- Improve the transformations, pipelines and workflows used to prepare data
- Work with the CFO to explain business performance through data
- Keep analytical systems dependable through checks for quality, observability and reproducibility
- Run experiments and use causal analysis to guide product choices with engineering and product teams
What you bring
- At least five years using Python and SQL
- Strong statistical analysis skills, including experimentation and causal inference
- Experience examining user behavior through measures such as A/B tests and conversion rates
- Hands-on familiarity with current data platforms and tools such as Redshift, Snowflake or dbt
Who this fits
You’ll suit work that calls for open-ended problem solving and ownership, with a focus on product and engineering decisions. The role is onsite in New York.
From the employer
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
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
Data Science work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
Data Science
Find me workBy the team behind dataroles.