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Senior Data Scientist, Product Data and Machine Learning

Senior Data Scientist, Product Data and Machine Learning

2 Days ago • 5-8 Years • Data Analyst

About the job

4 skills required for this role

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

data-structures

python

sql

cross-functional

Job Description

This Senior Data Scientist role at Google supports their billion-plus user base. You'll leverage your expertise in statistical analysis, data mining, and machine learning to optimize operational efficiency for internal teams. Responsibilities include performing analyses using SQL, R, and Python; reporting KPIs to leadership; building analytical business cases; designing and deploying machine learning models; collaborating with engineering on data collection and instrumentation; and solving ambiguous business problems. The ideal candidate possesses strong experience in the full ML lifecycle and a proven ability to communicate complex findings effectively.

Must have:

Master's degree in quantitative field
5+ years statistical data analysis experience
3+ years project management experience
SQL, R, Python proficiency
Machine learning model building & deployment
KPI reporting & business case development

Good to have:

5+ years experience in scripting and statistical analysis (R, Stata, SPSS, SAS)
Experience with the full ML product lifecycle
Experience building production ML pipelines
Applying ML solutions to enterprise operations

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Minimum qualifications:

Master's degree in Statistics, Economics, Engineering, Mathematics, a related quantitative field, or equivalent practical experience.
5 years of experience with statistical data analysis, data mining, and querying (e.g., SQL).
3 years of experience in managing projects.

Preferred qualifications:

5 years of experience in scripting, statistical analysis (e.g., R, Stata, SPSS, SAS), developing and managing metrics, and evaluating programs/products.
Experience with the full Machine Learning (ML) product lifecycle, from ideation to exploration, productionization, and support.
Experience in building production Machine Learning (ML) pipelines.
Experience applying Machine Learning (ML) and advanced analytics solutions to enterprise operations teams.

About the job

Help serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next.

In this role, you will help develop data-leveraged solutions that optimize the operational efficiency of internal stakeholder teams who equip users with the personal and collaboration technology they need to be productive. The team drives awareness with internal customers throughout the Corporate Engineering organization about how to effectively manage and use data for advantage, model critical business operations, and deploy AI/ML solutions. The team also provides quantitative support and are partners to the business by delivering data-driven insights and solutions.

Responsibilities

Perform analysis utilizing tools (e.g., SQL, R, Python), help solve problems, narrow down multiple options into the approach, and take ownership of open-ended ambiguous business problems to reach an optimal solution.
Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team.
Build and prototype analysis and business cases to provide insights, develop comprehensive knowledge of Google data structures and metrics, and advocate for changes needed for product development.
Design and develop machine learning models to solve problems within the Enterprise Support space, and work alongside Machine Learning Engineering teams to test and deploy generative AI models.
Collaborate with Engineering teams to identify and address instrumentation gaps, ensure accurate data collection for functionalities, and focus on customer journeys.

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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.