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Senior Data Scientist Research, Googler Technology and Engineering

Senior Data Scientist Research, Googler Technology and Engineering

2 Days ago • 3-8 Years • Data Analyst

About the job

5 skills required for this role

Test your skills to join the top 1% applicants for this job

unity

algorithms

python

sql

data-science

Job Description

This Senior Data Scientist Research role at Google focuses on developing data-driven solutions to optimize internal operations. Responsibilities include leading research projects exploring novel applications of data science and machine learning, designing and implementing sophisticated statistical and machine learning models, collaborating with ML engineers to create production-ready solutions, refining models through experimentation, and staying current on advancements in the field. The role involves working with various teams, providing data-driven insights, and using data to help make better business decisions. The ideal candidate will have significant experience in analytics, coding (Python, R, SQL), database querying, and statistical analysis, along with experience in the ML product lifecycle from ideation to production.

Must have:

Master's degree in quantitative field or equivalent experience
5+ years of experience using analytics to solve problems
Proficiency in coding (Python, R, SQL)
Experience with database querying and statistical analysis
Experience with ML product lifecycle
Lead research projects and develop data-driven solutions

Good to have:

PhD degree and 6+ years of experience
Experience applying ML solutions to enterprise operations
Experience building production ML pipelines

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Minimum qualifications:

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

Preferred qualifications:

8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
Experience with Machine Learning (ML) product lifecycle from ideation to exploration, productionization, and long-term support.
Experience applying ML and advanced analytics solutions to the enterprise operations team.
Experience building production ML pipelines.

About the job

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.

In this role, you will help develop data leveraged solutions that optimize the operational efficiency of our internal stakeholder teams. You will drive awareness with our internal customers throughout the corporate engineering organization about how to effectively manage and use data for strategic advantage, model critical business operations and deploy AI/ML solutions. You will provide quantitative support to strategic partners to the business by delivering data-driven insights and solutions. You will be using data to help them make better business decisions and weave stories with meaningful insight from data.

Responsibilities

Lead research projects that explore novel applications of data science and machine learning within our business.
Design, implement, and evaluate sophisticated statistical and machine learning models, pushing the boundaries of performance and efficiency in an enterprise environment.
Work with Machine Learning (ML) Software Engineers to translate research findings into scalable and production ready solutions.
Refine models and algorithms through experimentation and optimization and understand trade-offs and design choices.
Stay up-to-date on the latest developments in data science and machine learning research internally and externally, identify and evaluate new techniques and technologies.

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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.