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 benefits at Google [https://careers.google.com/benefits/].
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.
