Senior Data Scientist, Product, Payments

Minimum qualifications:

• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
• 8 years of experience with analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 5 years work experience with a Master's degree.
• 4 years of experience with databases, SQL coding with standard commercial databases (e.g., Teradata, MySQL), and statistics tools (e.g., R, Python).
• Experience in working on statistical/casual inference techniques across Experimentation and Observational studies.

Preferred qualifications:

• Experience with working in the Digital Ads or Payment industry.
• Experience in driving incrementality value estimation through causal methods.
• Experience as a business/quantitative analyst in e-commerce, payments or financial services.
• Ability to manage, organize work and a team of analysts, with excellent communication skills with executive management.

About the job

In this role, you will ensure that Google makes business and product decisions through data, evaluation and statistical analysis. You will be analyzing signal behavior to drive growth strategy, product excellence in signal quality, identifying headroom opportunities, tracking performance or building metrics that matter, is used by our leaders to make product decisions across various Payment consumer products.

Responsibilities

• Perform analysis utilizing related tools (e.g., SQL, R, Python). Help solve problems, narrow down multiple options into the best approach, and take ownership of open-ended business problems to reach an optimal solution.
• Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues.
  
• Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team. Translate analysis results to business insights or product improvement opportunities.
• Build and prototype analysis and business cases to provide insights. Develop knowledge of Google data structures and metrics, advocating for changes where needed for product development.
• Influence across teams to align resources and direction.