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Senior Business Data Scientist, Revenue Acceleration, Google Cloud

Senior Business Data Scientist, Revenue Acceleration, Google Cloud

2 Months ago • 4-6 Years • Data Analyst • Undisclosed

About the job

6 skills required for this role

Add these skills to join the top 1% applicants for this job

tensorflow

python

pytorch

sql

data-science

cross-functional

Job Description

The Revenue Acceleration team (RevX) at Google Cloud focuses on boosting growth using scalable, data-driven strategies. As a Senior Business Data Scientist, you'll solve complex problems using analytics, statistics, ML, and GenAI. Responsibilities include processing large datasets, extracting insights, partnering with stakeholders to understand analytical needs, communicating results effectively, building ML solutions, designing experiments, and researching new modeling techniques. You will collaborate with engineers, program managers, and other stakeholders to implement ML solutions, measure program effectiveness, and drive customer growth.

Must have:

Master's degree in quantitative discipline
4+ years Data Science experience
SQL, Python, TensorFlow/Pytorch proficiency
Cross-functional collaboration experience
Data analysis, ML solutions, experiment design

Good to have:

PhD in quantitative discipline
6+ years industry Data Science experience
Full data science development lifecycle experience
Experience working with non-technical users

Minimum qualifications:

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
4 years of experience in a Data Science role using statistics and machine learning to solve product or business problems.
4 years of experience using SQL and programming in Python, TensorFlow, or Pytorch.
Experience in cross functional collaboration, with program management, go-to-market, engineering, and/or product teams.

Preferred qualifications:

PhD in a quantitative discipline such as Computer Science, Engineering, Statistics, Economics, Operations Research, or equivalent practical experience.
6 years of industry experience in a Data Science role (4 years with PhD) using statistics and machine learning to solve product or business problems
Experience with the full technical development cycle of Data Science solutions including data sourcing and pre-processing, model development, refinement, and deployment.
Experience working in partnership with non-technical users to define requirements, explain technical concepts to business users, etc.
Experience in driving a project from an experimental idea to a proof-of-concept to a launched product feature.

About the job

The Revenue Acceleration team (RevX) is focused on boosting the growth of Google Cloud with scalable and data driven strategies. The team is highly cross-functional, combining Strategy and Operations and Data Science. The team serves many functions, including designing business workflows, improving business programs, and developing tools and incentive systems to accelerate business performance. As a Data Scientist on the Revenue Acceleration team, you will be solving difficult and non-routine problems by applying Analytics, Statistics, ML, and GenAI to achieve results. You will process, analyze, and interpret large and complex data sets, with emphasis in delivering data-driven insights and solutions. You will also collaborate closely with Engineers, Program Managers, and other stakeholders to implement ML solutions, measure the effectiveness of programs, and drive customer growth and success.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

Process large amounts of data from multiple sources and extract relevant insights.
Partner with non-technical stakeholders to understand their analytical needs, help frame the problem by asking the right questions, and prioritize requirements. Effectively communicate results of technical work to non technical audiences.
Produce actionable data-driven insights, perform statistical analyses, build Machine Learning solutions , and design experiments to measure the effectiveness of models, tools, and programs.
Research new ways of modeling data proactively to unlock actionable insights or improve business processes.

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About The Company

Google

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A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.