Senior Business Data Scientist, Behavioral Economics

2 Months ago • 4-6 Years

Job Summary

Job Description

As a Senior Business Data Scientist at Google, you'll leverage behavioral economics principles and advanced analytical skills to solve critical business problems. You'll work across various teams, including engineering, data science, and product, to build data pipelines, design experiments, and develop dashboards. Responsibilities include translating complex business challenges into actionable solutions, creating and maintaining large datasets, automating reports, and contributing to research projects. Your work will focus on understanding user behavior, enhancing advertising efficacy, and improving operational efficiency. You'll communicate findings and recommendations to senior executives and collaborate with cross-functional teams to implement impactful solutions. Fluency in English and Spanish is required.
Must have:
  • Master's degree in quantitative discipline
  • 4+ years analytics experience
  • Proficiency in Python, R, SQL
  • Data querying & statistical analysis
  • Fluent English & Spanish
  • Communicating insights to executives
Good to have:
  • PhD in relevant field
  • Experience with LLMs
  • Building data pipelines from diverse sources
  • Hypothesis testing and model performance analysis

Job Details


Minimum qualifications:

  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  • 4 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.
  • 6 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 Senior Business Data Scientist, 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).
  • Build and maintain large, organized datasets from complex, unstructured, and continuously changing data sources.
  • 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.
  • Contribute to a wide variety of research projects using data engineering, statistical analysis or machine learning methods.

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