招聘

Senior Data Scientist, Product, Customer Engagement Sales Intelligence
placeMountain View, CA, USA
·
On-site
·
Full-time
·
1mo ago
Compensation
$156,000 - $229,000
Benefits & Perks
•Parental leave program
•Remote work flexibility
•Annual team offsites
•Learning and development stipend
•Wellness benefits
Required Skills
TensorFlow
Python
SQL
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 Data Scientist in the Customer Engagement Data Science team, you will help drive the idea of how Google Ads builds customer success through a sales and customer intelligence engine, creating incremental value for Google.
The US base salary range for this full-time position is $156,000-$229,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Help solve problems, narrowing down multiple options into the best approach, and take ownership of open-ended ambiguous 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.
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Build and prototype analysis and business cases to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed for product development.
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Influence across teams to align resources and direction.
Minimum qualifications
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Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, a related quantitative field, or equivalent practical experience.
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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.
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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
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