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Data Science Analyst, Revenue Acceleration - Google

Google


Location:
Mountain View, California
Date:
03/16/2017
Categories:
  • Data Scientist
  • Data Analytics
  • Business Intelligence
  • Data Engineer
Google
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Job Details

The Business Strategy & Operations organization provides business critical insights using analytics, ensures cross functional alignment of goals and execution, and helps teams drive strategic partnerships and new initiatives forward. We stay focused on aligning the highest-level company priorities with strong day-to-day operations, and help evolve early stage ideas into future-growth initiatives.

The Revenue Acceleration team within Go-to-Market Operations is a global team that aligns the company business growth priorities with strong automation and analytics to deliver business growth opportunities to our sellers and customers. Specifically, we are responsible for the strategy, systems, and analytics that drive algorithmic lead generation (i.e., “Recommended Opportunities”) for our frontline teams. Through this, the team drives a substantial portion of Google’s Ads business and impacts the day-to-day operations of sales teams across the globe.

As a Data Science Analyst, you will work on building models ranking relevance of leads, deliver insights into the performance of Recommended Opportunities, and provide data-driven recommendations on how to improve the effectiveness and business growth performance of the program. With the team, you will analyze very large datasets to discern impact of different attributes on performance and unearth opportunities for improvement. You will work closely with diverse stakeholders, both global and regional, to also understand the context and behavioral elements that drive performance.

Sales Operations is the global team that makes sure Google's complex and ever-evolving business runs smoothly. Experts in leading process improvements and consistency, team members are analytical and strategic with a pragmatic sense of how to get things done. They develop global initiatives and set high-level goals to improve productivity.

 

Responsibilities

  • Conceptualize and build models to predict relevance of recommendations and improve their adoption resulting in overall improvement of the Recommended Opportunities program.
  • Execute complex business analyses on a global scale to help drive adoption and efficiency of the program.
  • Perform ad hoc analyses to drive understanding of the impact of several parameters and attributes on the program metrics.
  • Present analyses effectively to stakeholders and partners.

Requirements

Minimum qualifications:

  • Bachelor's degree in Math, Economics, Engineering or related quantitative field or equivalent practical experience.
  • 4 years of relevant work experience in statistical and predictive modeling, and analytics in a data environment that is revenue-facing or sales related.
  • Experience with statistical modeling tools such as R. Proficient in SQL, and scripting languages such as Python.
  • Experience with machine learning systems.

 

Preferred Qualifications:

  • Experience building recommendation models.
  • Track record of applying quantitative decision making techniques in a business setting.
  • Distinctive problem-solving and analysis skills, combined with strong business judgment.
  • Deep commitment to thoroughness and accuracy in analysis and reporting.
  • Excellent written and oral communication and interpersonal skills.

 

At Google, we don’t just accept difference - we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products and our community. 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. If you have a disability or special need that requires accommodation, please let us know.

 

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