채용
Benefits & Perks
•Remote work flexibility
•Health, dental, and vision coverage
•Flexible PTO policy
•Top Tier compensation with equity
Required Skills
TensorFlow
SQL
Apache Spark
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
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Understand Google Pay India products and technologies to influence the Product Roadmap with insights and data-motivated recommendations.
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Partner with leadership to set Objectives and Key Results (OKRs), drive growth, and lead planning, forecasting, and performance reviews across multiple markets.
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Utilize Generative AI techniques to enhance analytics productivity, automate reporting, and apply causal inference/Eval Frameworks for feature evaluation.
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Own the end-to-end analytics stack, from defining metrics and building data schemas with engineering teams, to executing experimentation and optimization.
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Lead global, and multi-market projects with framing solutions to solve data problems and optimize recommendation quality for improved end-user experience.
Minimum qualifications
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Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience.
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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.
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Experience with experiments and causal analysis with turning insights into product decisions.
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Experience with leading interactions and communications with executive management.
Preferred qualifications
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Experience with working in the payments, online e-commerce or marketplace industry.
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Experience in driving incrementality study or value estimation through causal methods.
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Experience as a business/quantitative analyst in e-commerce, payments or financial services environment.
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Ability to manage and organize work, and structure and lead investigative workstreams, analysis with collaborating for product decisions with Product Manager or Engineers.
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Ability to work in an unstructured environment with excellent partnership and cross-functional collaboration skills.
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About Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
Employees
Mountain View
Headquarters
$1,700B
Valuation
Reviews
3.7
25 reviews
Work Life Balance
3.8
Compensation
4.2
Culture
3.4
Career
3.9
Management
2.8
68%
Recommend to a Friend
Pros
Excellent compensation and benefits
Smart and talented colleagues
Great perks and work flexibility
Cons
Management and leadership issues
Bureaucracy and slow processes
Constantly changing priorities and reorganizations
Salary Ranges
63,375 data points
Junior/L3
L3
L4
L5
L6
L7
L8
Mid/L4
Principal/L7
Senior/L5
Staff/L6
Director
Junior/L3 · Data Scientist L3
0 reports
$176,704
total / year
Base
-
Stock
-
Bonus
-
$150,298
$203,110
Interview Experience
9 interviews
Difficulty
3.4
/ 5
Duration
14-28 weeks
Offer Rate
44%
Experience
Positive 0%
Neutral 56%
Negative 44%
Interview Process
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Product Sense
News & Buzz
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