About The Position

Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations. In this role, your primary mission is to help our Global Business Strategy and Operations (GBS&O) partners make the best possible decisions using data. You will own the full data science life-cycle for ambiguous business problems from initial analysis to recommendation. You will drive value across the full data spectrum, from core BI, data pipelining, and dashboarding to advanced causal and correlational modeling. Your primary focus will be transforming our Policy, Risk, and Compliance strategy, moving beyond analysis to produce and present insights that directly influence business outcomes. You will need the agility to pivot and deliver solutions as high-stakes business priorities evolve. 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/].

Requirements

  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

Nice To Haves

  • 6 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Experience with ads policy, risk, or compliance.

Responsibilities

  • Own the full data science life-cycle, applying your expertise in causal inference, predictive modeling, data infrastructure, and descriptive analytics to build frameworks that solve business problems.
  • Lead analytics and strategy for the Policy, Risk, and Compliance partner team, overseeing the process from data pipeline and tool design to advanced statistical analysis and the generation of insights.
  • Partner with stakeholders across StratOps and other Analytics teams to translate ambiguous, high-priority business problems into clear, data-driven strategies and decisions.
  • Address ambiguous problems by diving into messy datasets, then use your expert toolkit (e.g., SQL, R, and Python) to find creative, scalable solutions and build automated data pipelines, BI infrastructure, and dashboards from the ground up.
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