Data Analytics, Serotonin

• We're looking for a versatile data professional who combines strong analytical and data science capabilities with the engineering skills to build and maintain the infrastructure behind those analyses
• This is a hybrid role perfect for someone who loves both discovering insights and building scalable systems to deliver them
• Strong experience with modern data stack tools (e.g., dbt, Airflow/Dagster, Snowflake, BigQuery, Redshift, or similar)
• Proven ability to design and manage ETL pipelines and database architectures
• Advanced SQL skills and high proficiency in Python for both data analysis and engineering
• Understanding of data modeling principles (Kimball, Data Vault, or similar)
• Experience with cloud data platforms (AWS, GCP, or Azure)
• Strong statistical analysis skills with hands-on experience using Python data science stack (pandas, NumPy, scikit-learn)
• Experience with A/B testing, causal inference, and experimental design
• Ability to communicate complex findings to non-technical stakeholders
• Track record of using data to influence business strategy
• Hands-on experience with blockchain data extraction, transformation, and analysis
• Understanding of EVM concepts (transactions, events, smart contracts) and/or non-EVM ecosystems
• Ability to work with on-chain data to derive actionable insights
• Gets excited about both building robust data infrastructure AND discovering insights
• Wants ownership over the entire data value chain
• Thrives in environments where they can wear multiple hats
• Values being able to see their analyses through to production impact

Desirable

• You'll work across the entire data stack - from pipeline development to statistical modeling
• Build and maintain data pipelines that power both ad-hoc analyses and production dashboards
• Develop statistical models and data science solutions while also implementing the infrastructure to deploy them
• Create self-serve analytics tools and datasets that empower stakeholders across the organization
• Design experiments and perform statistical analyses to measure product and marketing initiatives
• Build data models in our warehouse that balance analytical flexibility with performance
• Partner directly with product, marketing, and leadership teams to identify opportunities and measure impact
• Own the full lifecycle of data products - from initial exploration to production deployment