The Analytics Manager will build and maintain data pipelines, develop statistical models, create self-serve analytics tools, and partner with teams to measure impact and identify opportunities within blockchain and Web3.
Who is Serotonin
Serotonin is the top go to market firm for transformative technologies, specializing in marketing, strategy, recruiting, and legal services. With a global team of 90 across 15 countries, Serotonin has supported over 300 clients in consumer tech, web3 infrastructure, digital assets, venture capital, and AI since its launch in 2020. Delivering end-to-end go-to-market solutions across all major marketing channels - including public relations, growth marketing, on-chain analytics, content, research, social, and design - Serotonin accelerates global innovation. At the core of our business is the Serotonin Platform, serving as a central nucleus for the web3 ecosystem, connecting builders and founders with essential resources to drive business growth.
About the Role
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. You'll work across the entire data stack - from pipeline development to statistical modeling. Leveling is flexible based on experience.
Responsibilities
- 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
Requirements: Core Technical Skills
- 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)
Requirements: Analytical & Data Science Expertise
- 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
Requirements: Blockchain & Web3 Experience
- 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
Bonus Points
- Experience with marketing analytics and attribution modeling
- Familiarity with data from providers like Dune, Arkham, GoldSky, Flipside, or similar
- Previous experience in data roles within blockchain/Web3 organizations
- Experience with data visualization tools (Tableau, Looker, or similar)
This position is ideal for someone who...
- 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
Benefits
- Competitive Salary
- Health Insurance - (US Only)
- 401(k) - (US Only)
- Remote Work Environment
- Maternity/Paternity Leave
Top Skills
Airflow
AWS
Azure
BigQuery
Dagster
Dbt
GCP
Looker
Numpy
Pandas
Python
Redshift
Scikit-Learn
Snowflake
SQL
Tableau
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