Data Scientist, Research, Google Display Ads Optimization

Minimum qualifications:

• Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
• 3 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
• 1 year of experience managing analytical projects.

Preferred qualifications:

• Ph.D. degree in relevant fields (Mathematics, Statistics, Computer Science).
• Ability to apply different models to solve problems.
• Excellent problem-solving skills.

About the job

At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.

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.

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 .

Responsibilities

• Work on areas such as Ads Retrieval, Ads Targeting, Auto Bidding, and prediction Machine Learning models.
• Identify key issues and develop solutions, along with statistical modeling skills to establish core metrics and build models that enhance bidding strategies.
• Work on projects which are a combination of engineering, machine learning, and data analysis.
• Improve ads retrieval model quality to maximize network business.
• Develop evaluation framework to better evaluate and understand ads early retrieval system.