Data Scientist, Data Quality and Benchmarking
Chainlink LabsFull Time
Junior (1 to 2 years)
Candidates should possess a Bachelor’s degree in Computer Science, Information Technology, or a related field, and have at least two years of experience in software testing. Proficiency in programming languages such as Python or Java, along with knowledge of SQL and data querying for data validation, is required. Familiarity with test automation tools and frameworks, version control systems like Git, and CI/CD tools is also necessary.
The Senior Big Data Test Development Engineer will be responsible for testing and quality assurance of big data and data-related products, participating in the development of big data testing frameworks, and contributing to the construction of continuous integration platforms and automation development. They will validate data quality, consistency, and accuracy across data pipelines, analyze test results, and provide detailed reports on software quality and test coverage. The role also includes monitoring and validating data workflows and pipelines, continuously improving testing processes, and ensuring data integrity and accuracy across various data sources and platforms, while collaborating closely with data engineers to improve data quality.
Intellectual property and innovation intelligence platform
PatSnap offers a platform that helps businesses, inventors, and researchers understand patents and innovation. Its main product aggregates and analyzes data from patents, scientific literature, and market reports, enabling clients to make informed decisions about their R&D investments. PatSnap operates on a subscription model, providing various service tiers and educational courses to empower clients in leveraging their innovation data. The company's goal is to help clients drive business growth and maintain a competitive edge through effective use of intellectual property.