Google Knowledge Graph Associate – Data focus, Remote

🏢 Google📍 Denver, CO, United States💼 Full-Time💻 Remote🏭 Internet Services💰 70000-95000 per year

About the Company

Google’s mission is to organize the world’s information and make it universally accessible and useful. We build products and services that improve the lives of billions of people. As a global leader in technology, we foster a culture of innovation, collaboration, and continuous learning. Our teams are at the forefront of tackling some of the most challenging problems in computer science and beyond, impacting everything from search to artificial intelligence. Join us and help shape the future of information.

Job Description

We are seeking a highly motivated and detail-oriented Google Knowledge Graph Associate to join our remote team. This role is crucial for enhancing the quality, accuracy, and comprehensiveness of the Google Knowledge Graph. You will be responsible for analyzing vast datasets, identifying patterns, correcting discrepancies, and ensuring the integrity of structured information that powers Google Search, Assistant, and other products. This is a data-focused role where your analytical skills will directly contribute to how billions of users discover and interact with information every day. This position offers the flexibility of working 100% remotely.

Key Responsibilities

  • Analyze and evaluate large datasets to identify data quality issues, inconsistencies, and areas for improvement within the Knowledge Graph.
  • Perform in-depth research to validate facts, entities, and relationships, ensuring accuracy and reliability of information.
  • Develop and apply robust data annotation and labeling guidelines to improve machine learning models and data extraction processes.
  • Collaborate with engineering and product teams to implement data quality improvements and provide insights for new features.
  • Monitor data performance metrics and proactively identify emerging data trends or potential issues.
  • Contribute to the development and refinement of data processing workflows and tools.
  • Stay updated on industry best practices for data management, structured data, and knowledge representation.

Required Skills

  • Strong analytical and problem-solving skills with meticulous attention to detail.
  • Proficiency in SQL for data querying and analysis.
  • Demonstrated understanding of structured data formats (e.g., JSON, XML) and principles of knowledge representation.
  • Excellent written and verbal communication skills in English.
  • Ability to work independently and manage multiple tasks effectively in a remote environment.
  • Experience with large-scale data analysis projects.

Preferred Qualifications

  • Bachelor's degree in Computer Science, Data Science, Linguistics, Information Systems, or a related quantitative field.
  • Experience with Knowledge Graphs, semantic web technologies (e.g., RDF, OWL), or linked data.
  • Familiarity with scripting languages such as Python or R for data manipulation.
  • Exposure to machine learning concepts or natural language processing (NLP).
  • Experience working in a fast-paced, global tech environment.

Perks & Benefits

  • Comprehensive medical, dental, and vision insurance.
  • Generous paid time off, including vacation, sick leave, and company holidays.
  • Remote-first culture with support for home office setup.
  • Opportunities for professional development and continuous learning.
  • Employee assistance programs and wellness resources.
  • 401(k) retirement plan with company match.
  • Parental leave and family support programs.
  • Access to Google's internal learning resources and communities.

How to Apply

If you are interested in this position, please click the "Apply Now" button below. To ensure your application is properly considered, please prepare the following:

  • An up-to-date Resume or CV
  • A brief cover letter summarizing your experience and motivation

Applications are reviewed on a rolling basis. Only shortlisted candidates will be contacted for an interview.

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