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职位Google

Product Data Scientist, FOP Optimization

Google

Product Data Scientist, FOP Optimization

Google

·

On-site

·

Full-time

·

2w ago

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.

As a Product Data Scientist for FOP Optimization, you will shape Payments products and solutions, helping our leaders make data-driven decisions. You will lead a critical part of the payments routing infrastructure, Smart Router, that utilizes machine learning and AI to process first-party transactions across Play, YouTube, Ads, and more. You will drive analytics for form of payment (FOP) optimization, building on success metrics, driving insights, and driving global launches. You will also play a critical role in our interactions on B2C analytics with Play and YouTube to optimize buyflows, purchase readiness, conversion, and UI on these critical Google products.

Responsibilities

  • Play a critical role in shaping the future of Google Payments by leveraging data and analytics to drive decisions, influencing strategy, and creating business impact across the organization.

  • Identify and solve ambiguous, high-stakes problems, transforming data into clear, actionable insights that directly influence leadership decisions (e.g., VPs and directors).

  • Lead complex projects that combine analytical precision with organizational strategy, delivering clear and actionable insights that inform tangible business decisions.

  • Contribute to the development and alignment of team OKRs and analytics strategy to ensure they support broader product and business goals across the Payments organization.

  • Collaborate cross-functionally with product, engineering, and operations teams to define key metrics and support data-driven decision making.

Minimum qualifications

  • Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.

  • 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 years of experience with a Master's degree.

Preferred qualifications

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

  • 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).

  • Experience in product analytics within payments, e-commerce, or financial services.

  • Ability to take initiative in unstructured environments with a bias for action and sharp attention to detail.

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关于Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

员工数

Mountain View

总部位置

$1,700B

企业估值

评价

3.7

25条评价

工作生活平衡

3.8

薪酬

4.2

企业文化

3.4

职业发展

3.9

管理层

2.8

68%

推荐给朋友

优点

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

缺点

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

薪资范围

57,502个数据点

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0份报告

$176,704

年薪总额

基本工资

-

股票

-

奖金

-

$150,298

$203,110

面试经验

9次面试

难度

3.4

/ 5

时长

14-28周

录用率

44%

体验

正面 0%

中性 56%

负面 44%

面试流程

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense