About the job

Google's leadership team hand-picks thorny business challenges, and members of Biz Ops 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.

As a Business Data Scientist, you will balance business and partner needs with technical constraints, develop innovative solutions and act as a partner and consultant to those you are working with. You will also build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects. You are focused on delivering excellent customer care and make sure things go smoothly for our customers across the globe when they need us most.

In g Tech Users and Products (gUP), our mission is to advocate for Google’s users by creating helpful and trusted experiences across the product ecosystem. We achieve this by meeting partners and consumers where they are with support and help, representing their needs with our product partners and proposing fixes and features that elevate their engagement with Google's diverse product ecosystem. Additionally we provide a range of product services that ensure our products are optimized for every user, no matter where they are in the world (e.g., localization, digitization, partner integration and more).

The US base salary range for this full-time position is $138,000-$198,000 + 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.

Responsibilities

• Translate business problems from your supported organization or functional area into problem-solving solutions and insights.

• Mentor technical teams in delivering project work including implementing data science solutions, improving data pipelines, developing evaluation metrics, or building statistical models that provide insights to the business.

• Design and implement reused and scaled solutions within the team's development process while analyzing impact on product or Google-wide metrics including daily activities, churn through close collaboration with product and engineering teams.

• Collaborate with consumer and engineering teams to write code and implement tools to improve troubleshooting efficiency and the end user experience.

• Manage stakeholder expectations and communicate with internal teams and external consumers, advertisers, and publishers to provide technical and business feedback as well as deliver technical solutions.

Minimum qualifications

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.

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

Preferred qualifications

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

• Knowledge of SQL, MySQL and Unix, Linux operating systems and commands.

• Ability to collaborate, build consensus, deliver, and drive technical decisions with various sized customer stakeholder groups.

• Ability to apply data analysis skills in a business context with demonstrated success in presenting datasets in a clear and compelling manner that inspires action.

• Excellent technical leadership, verbal and written communication, project management, problem-solving, and troubleshooting skills.