Senior Data Scientist Manager, Product, LearnX

1 Month ago • 7-15 Years • Data Analyst • $214,000 PA - $305,000 PA

Job Summary

Job Description

As a Senior Data Scientist Manager, Product, at LearnX (Google), you'll lead data science initiatives, providing quantitative support and strategic insights to partners. Responsibilities include performing analysis using tools like SQL, R, and Python; directing complex analytical projects; owning projects from problem definition to stakeholder presentation; and overseeing cross-functional project timelines. You'll guide teams, develop key metrics, innovate methodologies, and make critical recommendations to engineering and product management. This role blends technical expertise, strategic thinking, and leadership.
Must have:
  • Master's degree in quantitative field
  • 7+ years data analysis & project management experience
  • 5+ years data mining, SQL, metrics development
  • Perform analysis using SQL, R, Python
  • Direct complex analytical projects
  • Lead and impact contributions of others
Good to have:
  • 15+ years experience solving product/business problems
  • 6+ years people management in technical leadership role
Perks:
  • Bonus
  • Equity
  • Benefits

Job Details

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, and managing analytical projects.
  • 5 years of experience with data mining, querying (e.g., SQL), developing and managing metrics, and evaluating programs/products.

Preferred qualifications:

  • 15 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
  • 6 years of experience as a people manager within a technical leadership role.

About the job

Help 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.

As head of Data Science, you will play a important role in identifying/prioritizing key problems, developing key metrics, and innovating on new methodologies/tools to match the accelerating pace of innovation. This role requires a blend of technical expertise, strategic thinking, and team leadership.

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 $214,000-$305,000 + 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 .

Responsibilities

  • Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Direct projects that combine analytical and organizational complexity towards decisions.
  • Own projects, covering problem definition, metrics development, data extraction and visualization, creation, and implementation of statistical models, and presentation to stakeholders.
  • Address problems by using the capabilities of existing systems and collaborate to turn broad problems into work for the team.
  • Oversee the integration of cross-functional/organizational project/process timelines, drive improvements and recommendations, and define operational goals and objectives.
  • Provide direction and accomplish results through leading/impacting the contributions of others.

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