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, on-chain 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 crypto 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
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Build and maintain data pipelines that power both ad-hoc analyses and production dashboards
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Develop statistical models and data science solutions while also implementing the infrastructure to deploy them
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Create self-serve analytics tools and datasets that empower stakeholders across the organization
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Design experiments and perform statistical analyses to measure product and marketing initiatives
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Build data models in our warehouse that balance analytical flexibility with performance
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Partner directly with product, marketing, and leadership teams to identify opportunities and measure impact
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Own the full lifecycle of data products - from initial exploration to production deployment
Requirements: Core Technical Skills
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Strong experience with modern data stack tools (e.g., dbt, Airflow/Dagster, Snowflake, BigQuery, Redshift, or similar)
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Proven ability to design and manage ETL pipelines and database architectures
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Advanced SQL skills and high proficiency in Python for both data analysis and engineering
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Understanding of data modeling principles (Kimball, Data Vault, or similar)
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Experience with cloud data platforms (AWS, GCP, or Azure)
Requirements: Analytical & Data Science Expertise
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Strong statistical analysis skills with hands-on experience using Python data science stack (pandas, NumPy, scikit-learn)
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Experience with A/B testing, causal inference, and experimental design
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Ability to communicate complex findings to non-technical stakeholders
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Track record of using data to influence business strategy
Requirements: Blockchain & Web3 Experience
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Hands-on experience with blockchain data extraction, transformation, and analysis