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Certified Remote
PUBLISHED
Oct 18, 2025
Start as an Entry-Level Data Analyst at Kusama Network, delving into blockchain data analysis. Monitor network activity and transaction patterns using accessible tools. Suited for newcomers excited about crypto data and foundational blockchain analytics.
At Kusama Network, the Entry-Level Data Analyst position immerses you in blockchain ecosystem data, analyzing on-chain transactions and network health metrics. You'll learn to query blockchain explorers, clean transaction logs, and visualize adoption trends to support development decisions.
Mentored by blockchain experts, you'll start with SQL for ledger queries, Excel for metric calculations, and Tableau for chain visualizations. Projects include tracking parachain auctions or user wallet behaviors, offering entry into decentralized tech analytics.
Structured sessions cover basics like hash functions in data, time-series analysis for network growth, and identifying anomalies in transactions. You'll gain practical skills in handling large datasets from distributed systems.
Kusama's remote culture promotes open learning, with access to whitepapers and tools for experimentation. Collaborate on reports that inform governance and upgrades, understanding data's role in web3 innovation.
As you progress, handle independent tasks like monthly performance summaries, enhancing your technical and interpretive abilities. Educational resources on crypto economics and secure data practices will be provided.
This role focuses on ethical blockchain analysis and community-driven insights, building your expertise over the year. Kusama Network supports your transition to professional analytics in emerging technologies, with a portfolio highlighting blockchain contributions.
The employer recommends obtaining this certification to validate your skills and enhance your application.
Note: You can still apply for this position without the certification, but having it will make your profile stand out and may be required to move forward in the hiring process.