Business Data Scientist, gUP Analytics

About the job

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.

We are the analytics team, supporting gTech Users and Products (gUP) team, with key focus on:

• Elevating user needs and delivering insights to improve user experience with support and drive a successful product experience
• Leveraging ML/AI and Data Science to drive a seamless support experience by improving support resources, aligning support with user needs, and advocating user pain points to Product Areas (PAs)
• Enabling seamless experiences across products through scaled solutions, and elevates for cross-products user issues.

You will be supporting Knowledge, Information and Core vertical which spans products like Gemini, Search, Maps, Commerce, Assistant etc.

In gTech 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).

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $138000 - $197000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Work on data modeling, metric development, data prototyping, and insight generation using statistical techniques and machine learning.
• Work with engineering, operations, and marketing teams to identify areas to focus effort.
• Solve ambiguous problems and discover insights that drive operational, product, and marketing excellence.
• Ensure users have excellent product and service experiences.

  ure context.

Qualifications

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.
• 3 years of experience in end-user facing experimentation design.
• 3 years of experience with applied data science and statistical methods, machine learning algorithms and tools, or applied ML (e.g., deep learning, natural language processing, Large Language Model).

Preferred qualifications:

• PhD in a quantitative field such as Statistics, Engineering, or Sciences, or equivalent practical experience.
• Strong investigative and technical abilities to drive data analysis and insights for executive audiences (e.g., SQL, R, Python, dashboard creation, advanced statistical modeling) with attention to detail.
• Ability to craft engaging/compelling narratives in verbal and written communications for internal/external clients (e.g., executive stakeholders).
• Excellent organizational and project management skills with ability to manage multiple projects with competing priorities.