Senior Product Data Scientist, Customer Engagement

Socket.dev; Mountain View (CA); On-site; USD 163,000 - 236,000; Full time

Benefits offered by this job

Bonus target

Equity

Benefits

Job summary

Google is seeking a data-driven Data Scientist to support product and business decisions across Google's worldwide user base. You will provide quantitative support, market understanding, and strategic insight, turning data into actionable recommendations for Engineering, Product Management, and User Experience teams.

You'll design and analyze experiments (A/B tests), perform causal inference, and communicate findings to stakeholders to influence product direction.

Qualifications

• Bachelor's degree in a quantitative field or equivalent practical experience.
• 8 years analytics experience with statistics and coding (or 5+ years with a Master's).
• Experience with statistical data analysis, experimental design (A/B testing), and causal inference.

Responsibilities

• Define, own and refine product success metrics with PM/UX/Engineering for OKRs.
• Apply observational data analysis to address critical business questions.
• Collaborate with Engineering to address instrumentation gaps for accurate data collection.
• Understand data sets used by Customer Engagement and partner teams; plug gaps in logging.
• Improve experimentation velocity and analysis turnaround via self-service tools and processes.

Skills

Analytics

Statistical analysis

Coding (Python, R, SQL)

Education

Bachelor's degree or equivalent in a quantitative field

Master's degree (preferred)

Job description

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.
• 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years of work experience with a Master's degree).
• Experience with statistical data analysis, experimental design (e.g., A/B testing), and causal inference.

Preferred qualifications:

• Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.

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 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, and 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, Product Management, and User Experience. You relish analyzing the numbers one minute and communicating your findings to key stakeholders the next to influence product direction and quantify impact.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities:

• Define, own and refine product success metrics. Work with PM, UX, and Engineering to develop and maintain a comprehensive metric framework that ties to business priorities and contributes to annual and quarterly OKR settings.
• Apply technical expertise with observational data analysis to address critical business questions.
• Collaborate with Engineering teams to identify and address instrumentation gaps, ensuring accurate data collection for key functionalities, with a focus on our most impactful customer journeys.
• Build an understanding of the data sets used by Customer Engagement and its partner teams, and work with Engineering teams to plug gaps in logging and data infrastructure.
• Improve experimentation velocity and analysis turnaround time through adoption of self-service tools and improved processes.