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 ISO 9001 Certified | 400+ students | Learn more | by Metana | ||
Zinniađź“Ť Remote | $140k - $160k | |||
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Integrađź“Ť Remote | $79k - $85k | |||
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Dvtradingđź“Ť Remote | $130k - $170k | |||
Bluecubeservicesđź“Ť Remote | $79k - $87k |
Senior Data Scientist
Responsibilities
- Activiley shaping how company uses data for strategic decisions.
- Enhance data infrastructure and tooling for improved efficiency.
- Support critical business units with ad-hoc analytics and insights.
- Conduct deep-dive research and analysis to uncover actionable findings.
- Improve data collection and analytics processes across teams.
- Ensure dashboards provide clarity, usability, and real-time visibility.
Requirements
- Minimum 5+ years of experience in data science, data analytics, or related field.
- Proven track record of implementing data infrastructure improvements and optimisations.
- Prior experience working with blockchain tools or DeFi data strongly preferred.
- Strong proficiency in SQL, Python, and data visualisation tools.
- Experience with data warehousing, ETL processes, and data pipeline optimisation.
- Understanding of statistical concepts and practical experience applying them.
- Ability to translate complex findings into clear, actionable insights.
- Collaborative mindset with excellent communication skills to work effectively across teams.
What does a data scientist in web3 do?
A data scientist in web3 is a type of data scientist who focuses on working with data related to the development of web-based technologies and applications that are part of the larger web3 ecosystem
This can include working with data from decentralized applications (DApps), blockchain networks, and other types of distributed and decentralized systems
In general, a data scientist in web3 is responsible for using data analysis and machine learning techniques to help organizations and individuals understand, interpret, and make decisions based on the data generated by these systems
Some specific tasks that a data scientist in web3 might be involved in include developing predictive models, conducting research, and creating data visualizations.