Senior Data Scientist, Research, Chrome

1 Month ago • 3-8 Years • Data Analyst • $166,000 PA - $244,000 PA

Job Summary

Job Description

The Senior Data Scientist, Research, Chrome will collaborate with cross-functional teams to address product and business challenges within Chrome. Responsibilities include translating business questions into analytical models, designing and evaluating models using advanced statistical methods, gathering and preparing data from various sources (SQL, R, Python), and extracting insights to enhance user experience. This role requires expertise in statistical modeling, machine learning, and data manipulation. The position involves working with complex datasets and organizational sources to drive data-informed innovation within Google's Chrome browser.
Must have:
  • Master's degree in a quantitative field
  • 5+ years experience in data analytics
  • Proficiency in Python, R, SQL
  • Advanced statistical modeling skills
  • Data extraction and manipulation
  • Collaboration with stakeholders
Good to have:
  • PhD degree
  • 8+ years of experience
  • Experience with large datasets
  • Machine learning expertise
  • Human eval and experimentation
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details


Minimum qualifications:

  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
  • 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.

Preferred qualifications:

  • 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.

About the job

Chrome’s mission is to make the web work better for you. We do this by evolving Chrome, which serves the world and Google as both a product for users and a platform (i.e. Chromium and related components that advance the open web and open media technologies). Your work will have tremendous impact throughout Chrome, as you have an opportunity to work with the many teams that use our systems to gate features and understand users. As a platform, Chrome envisions a fast, safe, capable platform and growing web for generations of users and developers. As a product, Chrome imagines a more helpful, adaptive agent that helps people with their multifaceted needs. Chrome's goal is to redefine browsing by delivering unparalleled safety, speed, efficiency, and ease of use, and integrating with GenAI and Google's web products, to understand user needs and provide personalized experiences.

Our Data Science team blends research and product expertise to address challenges. We leverage a mix of theoretical and practical knowledge in advanced statistical, machine learning techniques, predictive modeling, human eval, experimentation, forecasting, exploratory analysis, and more to drive data-informed innovation, unlock opportunities, and enhance user experiences within Chrome.

The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .

Responsibilities

  • Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.
  • Leverage advanced statistical methods on complex datasets to extract insights from events and features across organizational sources.

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