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Staff Data Scientist, Product, Workspace

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Kirkland, WA, USA; New York, NY, USA; Durham, NC, USA; Raleigh, NC, USA. Minimum qualifications: • Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience. • 7 years of experience with statistical data analysis.• 6 years of experience conducting A/B tests to drive improvement of product metrics.• 5 years of experience with data mining, querying, and managing investigative projects.• 3 years of experience developing and managing metrics or evaluating programs/products.Preferred qualifications:• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.• 12 years of experience solving product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.Workspace is a cloud-based productivity suite that is revolutionizing the way people communicate and collaborate with one another. Workspace includes products like Gmail, Calendar, Meet, Documents, Sheets, Slides, Drive and many more. It serves over three billion active users across the globe, it shapes people’s experience at home, school and work. With traditional work models being disrupted by the pandemic, this is an exciting time to join an innovative team and help us define the future of hybrid work.Google is an engineering company at heart. We hire people with a broad set of technical skills who are ready to take on some of technology's greatest challenges and make an impact on users around the world. At Google, engineers not only revolutionize search, they routinely work on scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From Google Ads to Chrome, Android to YouTube, social to local, Google engineers are changing the world one technological achievement after another.The US base salary range for this full-time position is $168,000-$252,000 + 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 aboutbenefits at Google.Responsibilities• Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Provide leadership through proactive and strategic contributions (e.g., suggests new analyses, infrastructure or experiments to drive improvements in the business).• Own outcomes for projects by covering problem definition, metrics development, data extraction and manipulation, visualization, creation, and implementation of investigative/statistical models, and presentation to stakeholders.• Develop solutions, lead, and manage problems that may be ambiguous and lacking clear precedent by framing problems, generating hypotheses, and making recommendations from a perspective that combines both, problem-solving and product-specific expertise.• Oversee the integration of cross-functional and cross-organizational project/process timelines, develop process improvements and recommendations, and help define operational goals and objectives.• Oversee the contributions of others and develop colleagues’ capabilities in the area of specialization.Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See alsoGoogle's EEO Policy andEEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing ourAccommodations for Applicants form.
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$168000K
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What You Should Know About Staff Data Scientist, Product, Workspace, Google

Join Google's innovative team in Durham, NC as a Staff Data Scientist for the Product Workspace, where you can make a real impact on over a billion users. In this dynamic role, your passion for data will shine as you provide quantitative support, market understanding, and strategic insights to various partners within the organization. With a Master’s degree in Statistics, Mathematics, or a related quantitative field, coupled with extensive experience in statistical analysis and A/B testing, you will leverage your expertise to enhance product metrics effectively. You will craft compelling narratives from complex datasets, guiding critical recommendations for your fellow Googlers in Engineering and Product Management. The Workspace suite is transforming how the world collaborates, featuring tools like Gmail, Calendar, and Drive. As traditional work models shift, there's never been a better time to contribute to defining the future of hybrid work. Google appreciates individuals with diverse technical skills and a proactive approach to tackling technology’s toughest challenges. If you’re ready to be part of a team that’s changing the world—one insight at a time—this is the opportunity for you. In return, Google offers a competitive salary range from $168,000 to $252,000, plus bonuses, equity, and comprehensive benefits. Come share your passion with us!

Frequently Asked Questions (FAQs) for Staff Data Scientist, Product, Workspace Role at Google
What are the responsibilities of a Staff Data Scientist at Google in Durham, NC?

As a Staff Data Scientist at Google in Durham, NC, you will take ownership of projects and lead analyses using tools like SQL, R, and Python. Your responsibilities will include defining problems, developing metrics, managing data extraction, creating visualization models, and presenting your findings to stakeholders to drive improvements across the business. You'll also oversee cross-functional projects, contribute to process improvements, and enhance the capabilities of team members in your area of expertise.

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What qualifications are needed for the Staff Data Scientist position at Google?

To qualify for the Staff Data Scientist position at Google, you should have a Master’s degree in Statistics, Mathematics, or a related quantitative field, alongside significant professional experience. Specifically, you need at least 7 years of experience in statistical data analysis, 6 years in A/B testing, and 5 years in data mining and project management. Expertise in programming languages such as Python, R, or SQL is essential, with a preference for candidates who possess around 12 years of directly related experience.

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How does the Staff Data Scientist at Google contribute to product development?

The Staff Data Scientist at Google plays a critical role in product development by offering substantial analytical insights that drive decision-making. You will analyze user data and product metrics, conduct A/B tests, and craft compelling data narratives that help engineers and product managers understand user behavior and market trends, ultimately guiding improvements and innovations in Google's Workspace products.

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What tools and technologies should a Staff Data Scientist at Google be proficient in?

For the Staff Data Scientist role at Google, proficiency in data analysis and programming tools is crucial. You should be well-versed in SQL for data querying, and skilled in statistical programming languages such as R and Python. Familiarity with data visualization tools and frameworks to present your findings effectively to stakeholders will also be highly beneficial in making a lasting impact on project outcomes.

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What can I expect in terms of compensation as a Staff Data Scientist at Google?

As a Staff Data Scientist at Google, you can expect a competitive US base salary range between $168,000 and $252,000, depending on factors like your work location and level of experience. Additionally, this position offers performance bonuses, equity options, and comprehensive benefits, providing a well-rounded compensation package that reflects your contributions and expertise.

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Common Interview Questions for Staff Data Scientist, Product, Workspace
Can you describe your experience with statistical analysis as a Staff Data Scientist?

When answering this question, highlight your past roles and focus on specific statistical techniques you've applied, including regression analysis or A/B testing. Discuss how your analyses contributed to product improvements and decision-making, showing your understanding of both data and business.

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How do you approach A/B testing in your projects?

Explain your methodology for A/B testing, including how you define success metrics, set up control groups, and analyze the results. Provide an example where your testing provided valuable insights that led to measurable improvements in a product.

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What programming languages are you proficient in relevant to data science?

List the programming languages you have experience with, particularly Python, R, and SQL. Share specific projects or tasks where you applied these languages and highlight any libraries or frameworks you used, emphasizing your technical skills relevant to the Staff Data Scientist role.

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Tell me about a time you presented complex data findings to non-technical stakeholders.

Share a specific example where you simplified complex analytics and presented it effectively to a diverse audience. Highlight your ability to communicate insights clearly and how this benefited the team in decision-making processes.

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How do you prioritize your data projects?

Discuss your process for identifying and prioritizing data projects based on business needs and potential impact. Explain criteria you consider and how you balance competing requests, demonstrating your strategic thinking in the role.

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What experience do you have managing cross-functional collaborations?

Describe previous experiences where you worked closely with different teams, such as engineering or product management. Emphasize how you coordinated efforts, shared insights, and contributed to successful outcomes on cross-functional initiatives.

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How do you stay updated with data science trends and technologies?

Mention specific resources you use, such as online courses, webinars, or professional networks. Highlight your proactive approach to continuous learning and adapting to new trends or tools in data science, which is essential for a Staff Data Scientist.

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Can you give an example of a challenging data problem you've solved?

Describe a specific challenge you faced and the steps you took to resolve it. Focus on your analytical skills and mindset, discussing how you applied creative problem-solving to derive a solution that produced positive business outcomes.

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What methods do you use for data visualization?

Talk about the tools and techniques you commonly use for data visualization, such as Tableau, Power BI, or custom solutions in Python. Emphasize your ability to create compelling visuals that communicate complex data insights effectively to various stakeholders.

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How do you handle ambiguity in data projects?

Explain your approach to dealing with ambiguous situations, such as developing hypotheses, defining clear objectives, and leveraging collaboration where necessary. Highlight your analytical thinking and adaptability as traits that enable successful navigation of uncertainties in data science.

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CULTURE VALUES
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Take Risks
Collaboration over Competition
Growth & Learning
Transparent & Candid
Customer-Centric
Social Impact Driven
Rapid Growth
Passion for Exploration
Dare to be Different
Reward & Recognition
Friends Outside of Work
BENEFITS & PERKS
Medical Insurance
Dental Insurance
Vision Insurance
Mental Health Resources
Life insurance
Disability Insurance
Health Savings Account (HSA)
Flexible Spending Account (FSA)
Conferences Stipend
Bias Training
Employee Resource Groups
401K Matching
Paternity Leave
Maternity Leave
Some Meals Provided
Social Gatherings
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Full-time, on-site
DATE POSTED
December 12, 2024

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