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Data Scientist, Research, Real World Journeys (Portuguese, English)

Google is a global technology leader that specializes in internet-related services and products, including search, cloud computing, software, and hardware.
Data
Mid-Level Software Engineer
In-Person
3+ years of experience
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Description For Data Scientist, Research, Real World Journeys (Portuguese, English)

At Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution.

Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day. Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

As a Data Scientist in the Research, Real World Journeys team, you will be working on cutting-edge research projects that have the potential to shape the future of technology. You'll be analyzing complex datasets, developing innovative models, and collaborating with cross-functional teams to drive insights that can be applied to Google's products and services. This role requires a strong background in statistics, data science, and programming, as well as the ability to communicate complex findings to both technical and non-technical stakeholders.

Your work will directly contribute to improving user experiences, optimizing products, and driving business decisions. You'll have the opportunity to work on challenging problems in areas such as machine learning, natural language processing, and computer vision, all while leveraging Google's vast resources and data infrastructure.

Join us in this exciting role where you'll be at the forefront of technological innovation, working with world-class researchers and engineers to solve some of the most complex problems in the tech industry. Your contributions will help shape the future of Google's products and services, impacting millions of users worldwide.

Last updated 9 months ago

Responsibilities For Data Scientist, Research, Real World Journeys (Portuguese, English)

  • Collaborate with stakeholders in cross-project and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
  • Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
  • Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
  • Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.

Requirements For Data Scientist, Research, Real World Journeys (Portuguese, English)

Python
  • Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.
  • 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree.

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