| Job Position | Company | Posted | Location | Salary | Tags |
|---|---|---|---|---|---|
OP Labs | Remote | $103k - $117k | |||
OKX | Singapore, Singapore | $54k - $62k | |||
Bitso | Latin America | $72k - $103k | |||
Impossible Cloud | Remote | $62k - $67k | |||
| Learn job-ready web3 skills on your schedule with 1-on-1 support & get a job, or your money back. | | by Metana Bootcamp Info | |||
Advanced Blockchain AG | Remote | $75k - $110k | |||
Circle | Salt Lake City, UT, United States | $147k - $195k | |||
Lemon.io | Canada | $48k - $110k | |||
Blockchain.com | London, United Kingdom | $76k - $100k | |||
Gramercy Park Capital | New York, NY, United States |
| |||
Binance | Taipei, Taiwan |
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BitGo | Bengaluru, India | $98k - $103k | |||
Ripple | San Francisco, CA, United States | $73k - $93k | |||
Binance | Taipei, Taiwan |
| |||
Circle | Salt Lake City, UT, United States | $147k - $195k | |||
Binance | Taipei, Taiwan |
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What are the role responsibilities?
- Collaborating with business teams to design systems architecture:
- Design and implement robust, scalable, and optimized data architectures.
- Lead the development and maintenance of scalable data pipelines and build out new integrations to support continuing increases in data volume and complexity.
- Pipeline ownership:
- Develop integrations with third party systems to source, qualify and ingest various datasets.
- Develop data set processes for data modeling and production.
- Recommend and implement ways to improve data reliability, efficiency, and quality.
- Data strategy and execution:
- Work with stakeholders including the Marketing, Product, Analytics, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- BI and data tool enablement:
- Enable data analytics and visualization tools to extract valuable insights from the data to enable data-driven decisions
- Innovation and improvement:
- Keep up-to-date with the latest industry trends in data engineering.
- Explore new technologies and approaches for continuous improvement of data systems.
- Collaboration and communication:
- Work closely with analytics and business teams to define and refine data requirements for various data and analytics initiatives.
- Ensure clear communication of project progress and results to stakeholders.
- Collaborate with data engineers across the wider OP stack and ecosystem to enable open source and publicly available datasets.
What skills do you bring?
- 4+ years of professional data engineering experience
- Advanced working knowledge of SQL, Python, and experience with relational databases
- Experience in building and optimizing 'big data' data pipelines, architectures, and data sets
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with workflow orchestration management such as Airflow, dbt etc.
- Experience with Cloud Services such as Google Cloud Services, AWS, etc.
- Strong analytic skills related to working with unstructured datasets, we are looking for an engineer who can understand the business and how to build to requirements
- Excellent communication skills with the ability to engage, influence, and inspire partners and stakeholders to drive collaboration and alignment
- Self-starter who takes ownership, gets results, and enjoys the autonomy of architecting from the ground up
- Experience with web3 and blockchain protocols is a plus
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.