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Google
Google

Organizing the world's information and making it universally accessible.

Product Data Scientist Manager, Play Apps

RoleData Science
LevelLead
WorkOn-site
TypeFull-time
Posted1 month ago
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About the job

As a Product Data Science Manager in the Play Apps team, you will collaborate with stakeholders across Play Apps to define metrics and lead a team of data scientists to deliver impactful analysis. You will be responsible for setting the team's goal, priorities, and roadmap to support our partner Product Management and Engineering teams. You will play an integral role in setting Objectives and Key Results (OKRs) for partner work streams and providing thought leadership to unlock insights. The artifacts your team develops will be key inputs for product development and operational decisions.

In this role, you will lead and mentor data scientists to deliver strategic insights and high-quality data models that influence product and business strategy, enabling teams to make critical decisions that delight users and grow our business.

Responsibilities

  • Define team roadmap and prioritization, coordinate resources, provide technical leadership in-line with the long-term objectives, support and develop the team through mentorship and ongoing feedback.

  • Provide investigative thought leadership through proactive and strategic contributions, consistently use insights and analytics to guide decisions and alignment throughout the organization.

  • Define product success metrics and provide problem-solving Point of View (PoV) in various performance/strategic reviews. Synthesize insights across multiple investigative projects to provide investigative recommendations to influence and manage the development of overall, long-term product development strategies.

  • Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.

  • Anticipate and proactively address investigative challenges as a trusted authority and critical domain expert. Separately conduct problem framing through to impact problem-solving, including analysis and business cases.

Minimum qualifications

  • Bachelor'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) or 8 years of experience with an advanced degree.

  • 3 years of experience as a people manager within a technical leadership role.

Preferred qualifications

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

  • Experience in identifying opportunities for business/product improvement, defining/measuring the success of those initiatives, and effectively collaborating with Cross-functional (xFN), Cross-Product Area (xPA) teams.

  • Experience in one or more of these methods, such as statistical and causal inference, classification methods.

  • Experience in developing ML models, innovative methods, analysis and approaches.

  • Experience in e-commerce.

  • Strong communication and presentation skills to deliver findings of analysis.

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About Google

Google

Google

Public

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

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

10 reviews

4.5

10 reviews

Work-life balance

3.2

Compensation

4.3

Culture

4.1

Career

4.2

Management

3.8

82%

Recommend to a friend

Pros

Great benefits and perks

Innovative and interesting work

Career development and learning opportunities

Cons

High pressure and expectations

Long hours and heavy workload

Fast-paced and overwhelming environment

Salary Ranges

57,503 data points

Junior/L3

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

Junior/L3 · Data Scientist L3

0 reports

$176,704

total per 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