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Minimum qualifications:
Preferred qualifications:
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.
Responsibilities
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Senior Data Scientist, Product, Google Pay
Full Time
Singapore
Mid Level
World Class Benefits
Description
Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.
Minimum qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience.
- 8 years of experience with using 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.
- Experience with experiments and causal analysis with turning insights into product decisions.
- Experience with leading interactions and communications with executive management.
Preferred qualifications:
- Experience with working in the payments, online e-commerce or marketplace industry.
- Experience in driving incrementality study or value estimation through causal methods.
- Experience as a business/quantitative analyst in e-commerce, payments or financial services environment.
- Ability to manage and organize work, and structure and lead investigative workstreams, analysis with collaborating for product decisions with Product Manager or Engineers.
- Ability to work in an unstructured environment with excellent partnership and cross-functional collaboration skills.
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 to define Payments products. You will help to leverage data, conduct analysis and make business recommendations, coordinating across functions to help build business models. You will focus on adopting Generative AI technologies and adopting novel evaluation and investigative techniques for Generative Artificial Intelligence (AI) solutions. You will manage multiple projects at a time, focusing on the details and identifying ways to take on tests.
Responsibilities
- Understand Google Pay India products and technologies to influence the Product Roadmap with insights and data-motivated recommendations.
- Partner with leadership to set Objectives and Key Results (OKRs), drive growth, and lead planning, forecasting, and performance reviews across multiple markets.
- Utilize Generative AI techniques to enhance analytics productivity, automate reporting, and apply causal inference/Eval Frameworks for feature evaluation.
- Own the end-to-end analytics stack, from defining metrics and building data schemas with engineering teams, to executing experimentation and optimization.
- Lead global, and multi-market projects with framing solutions to solve data problems and optimize recommendation quality for improved end-user experience.