Business Data Science Lead, Behavioral Economics

1 Month ago • 7-9 Years • Data Analyst

Job Summary

Job Description

As a Business Data Science Lead, Behavioral Economics, you'll leverage scientific and statistical methods to analyze massive datasets, uncovering opportunities for Google to enhance efficiency and user understanding. You'll collaborate with multidisciplinary teams (data scientists, engineers, product managers, etc.) to translate findings into actionable strategies. Responsibilities include developing data pipelines, conducting statistical analysis, building machine learning models, and creating insightful reports and dashboards. You'll work on diverse projects, focusing on user behavior and translating business problems into analytical solutions, including experiments and bespoke datasets. You'll also actively contribute to research projects and advocate for data structure and metric improvements.
Must have:
  • Master's degree in quantitative discipline
  • 7+ years analytics experience solving business problems
  • Proficiency in Python, R, SQL
  • Fluent in English and Spanish
  • Data analysis and interpretation skills
Good to have:
  • PhD in relevant quantitative field
  • Experience with LLMs and machine learning model performance analysis
  • Experience building data pipelines using diverse user data
  • Experience with hypothesis testing

Job Details


Minimum qualifications:

  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Ability to communicate in English and Spanish fluently to interact with local stakeholders.

Preferred qualifications:

  • PhD in Statistics, Computer Science, Mathematics, or a quantitative social science such as Economics, Psychology, Political Science, or equivalent practical experience.
  • 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  • Experience articulating business/research questions, designing analysis frameworks, sourcing/creating the necessary data, using hypothesis testing, and translating analysis results into business recommendations.
  • Experience building data pipelines using different types of user data, including survey and open-text responses, product logs, etc.
  • Experience with analyzing machine learning model performance or working on Large Language Models (LLMs).

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.

As a Business Data Science Lead, you will work all across the organization to shape Google's business and technical strategies by creating, processing, analyzing, and interpreting huge datasets. Using investigative and statistical methods, you will use data to identify opportunities for Google to operate more efficiently, from enhancing advertising efficacy to improving our understanding of user behavior. You will work with a multi-disciplinary team of data scientists, engineers, product managers, sales associates, and marketing teams to adjust Google's practices according to your findings. You will also have to identify the problems and will figure out the solution.

In this role, you will bring scientific and statistical methods to test the data pipelining and product development, with a focus on the behaviors of end users. Through your professional expertise and judgment, you will work on multiple projects concurrently, developing datasets, analyses, models, and methods to support and verify the impact of your recommendations.

Responsibilities

  • Work with engineering, data science, and business collaborators to translate non-routine, interdisciplinary business problems into investigative solutions (e.g., pipelines, experiments, bespoke datasets, dashboards or machine learning models).
  • Work with large, datasets to develop answers for real world, large-scale business problems.
  • Contribute to a wide variety of research projects using data engineering, statistical analysis or machine learning methods.
  • Develop and automate reports, and iteratively build and prototype dashboards to provide insights at scale, solving for analytical needs.
  • Build analysis pipelines iteratively to provide insights at scale, and develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.

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