As a Data Scientist III at Google, you'll evaluate and improve Google's display ad products. You'll collaborate with engineers and analysts to solve complex problems, applying scientific excellence and statistical methods.  Responsibilities include identifying and clarifying business questions, designing and evaluating mathematical models, gathering and analyzing data using SQL, R, and Python, and owning projects from problem characterization to A/B testing and launch.  The role requires expertise in large-scale machine learning model development and deployment for real-time applications.  A Master's degree in a quantitative field or equivalent experience is required, with a PhD or 5+ years of experience preferred.

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<div jscontroller="iYVHDc" class="DkhPwc" jsname="tIk9qd" data-id="99097141716099782" jsaction="A6AxKc:CXOOvf;"><div class="KwJkGe"><h3>Minimum qualifications:</h3><ul>
<li>Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field or equivalent practical experience.</li><li>3 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.</li>
</ul><br><h3>Preferred qualifications:</h3><ul>
<li>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 a PhD degree.<br></li>
<li>4 years of industry experience, developing large-scale Machine Learning models for real-world problems and deploying them for real-time applications.<br></li>
<li>Experience with end-to-end project ownership, ranging through all stages such as problem characterization through empirical data analysis, solution conceptualization, implementation of offline modeling and online serving modules, A-B experimentation for impact measurement, and launch steering.</li>
</ul></div><div class="aG5W3"><h3>About the job</h3><p>As a Data Scientist, you will evaluate and improve Google's products. You will collaborate with a multi-disciplinary team of engineers and analysts on a wide range of problems. This position will bring scientific excellence and statistical methods to the challenges of product creation, development and improvement with an appreciation for the behaviors of the end user.<br></p>The US base salary range for this full-time position is $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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. <div><br></div><div>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 .<p><b></b></p></div></div><div class="BDNOWe"><h3>Responsibilities</h3><ul>
<li>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.<br></li>
<li>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.<br></li>
<li>Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.<br></li>
<li>Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.<br></li>
</ul></div></div>

Data Scientist III, Research, Display Ads