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Business Data Scientist, Marketing

Google

Business Data Scientist, Marketing

Google

·

On-site

·

Full-time

·

1w ago

  • Use your knowledge of data analytics to develop solutions for marketing challenges, while also uncovering opportunities for measurement and optimization to push brand and performance marketing to the next level.

  • Build measurement plans, tracking requirements, reporting, metrics and benchmarks for our largest campaigns to understand the incremental impact of our marketing dollars. (e.g. conversion lift tests, matched market analyses, and brand lift studies).

  • Partner with internal teams in advanced analytics work including experimentation, measurement and modeling.

  • Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results.

  • Develop evaluation frameworks for models, new metrics, and investigate anomalies. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods.

Google's leadership team hand-picks thorny business challenges, and members of Biz Ops work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.

As a Data Scientist in the Marketing team, you will drive key measurement and analytics programs that deliver a scaled impact for Google Marketing across media campaigns.

You will support the team by delivering pieces of project work including supporting the implementation of data science solutions, supporting the improvement of data pipelines, running geo-experiments or Marketing Mix Models (MMM) or helping your team develop evaluation metrics that provide insights to the business. You will own measurement and define milestones, provide direction for agencies/vendors, delegate, prioritize, plan, and direct a group of people to drive the project to completion.

You will play a strategic and technical role in managing all things media, marketing, analytics, and partnering with internal teams to evaluate strategic initiatives. Using first-party and third-party data sources, you will create innovative solutions to demonstrate the effectiveness of Google’s media investment. At Google-scale, this implies working on our industry’s challenges. You will maintain global consistency, while keeping regional focus. You will be working with teams operating across regions and marketing entities.

  • Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.

  • 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical 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

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

57,502 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 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