Quantitative Marketing Analyst, Consumer Apps Growth Marketing

1 Month ago • 3 Years + • Data Analyst

Job Summary

Job Description

As a Quantitative Marketing Analyst, you'll play a crucial role in understanding and optimizing the usage and subscription lifecycle for high-growth potential Google products. This role goes beyond traditional marketing analytics; you'll be at the forefront of experimentation, constantly testing and refining strategies to optimize the user journey. Collaborating with marketing, product, and engineering teams, you'll define key metrics, design experiments, and translate data into actionable recommendations impacting product development and marketing campaigns. Responsibilities include in-depth analysis of user behavior, creating reports and dashboards, designing and implementing A/B tests, building predictive models, and working with cross-functional teams to translate data insights into actionable recommendations. Fluency in English and Spanish is required.
Must have:
  • Bachelor's degree in quantitative field
  • 3+ years analytical experience
  • A/B testing experience
  • SQL, Python, or R proficiency
  • Cross-functional collaboration
  • Fluent in English and Spanish
Good to have:
  • Master's degree
  • R/Python for data visualization
  • Growth experimentation experience
  • Data pipeline building
  • Excellent communication skills

Job Details


Minimum qualifications:

  • Bachelor's degree in a research or quantitative field (e.g., Social Sciences, Statistics, Mathematics, Economics, etc.) or equivalent practical experience.
  • 3 years of work experience as analyst or in an analytical role (e.g. statistical analysis, querying databases, coding in SQL, Python, R).
  • Experience working cross-functionally with various stakeholders and teams.
  • Experience with designing and analyzing A/B tests, multivariate experiments, or other controlled studies.
  • Ability to communicate in English and Spanish fluently to support client relationship management in this region.

Preferred qualifications:

  • Master’s degree in a research or quantitative discipline.
  • Experience with R or Python for statistical analysis and data visualization.
  • Experience with growth experimentation.
  • Experience building data pipelines using different types of user data, including survey and open-text responses, product logs, etc.
  • Excellent SQL skills and the ability to write complex queries, extract data from various sources, and perform in-depth analysis.
  • Excellent communication skills. Ability to convince business stakeholders and communicate complex analysis insights to non-technical audiences.

About the job

The Subscriptions and Customer Growth Marketing organization drives consumer apps and subscription growth. We partner with product engineering and insights to understand the user and bring helpful products to market while deepening the consumer relationship. We’re passionate about showing consumers how to get more out of their favorite Google subscriptions and consumer apps.

As a Marketing Analyst, you will play a pivotal role in understanding and optimizing the usage and subscription lifecycle for high growth potential products.

In this role, you'll go beyond traditional marketing analytics. You'll be at the forefront of experimentation, constantly testing and refining strategies to optimize the entire user journey. By collaborating closely with marketing, product, and engineering teams, you'll help define key metrics, design experiments, and translate data into actionable recommendations that directly impact product development and marketing campaigns.

Responsibilities

  • Conduct in-depth analysis of user and subscriber behavior, identify trends, and uncover insights that drive product improvements and marketing strategies.
  • Create clear and informative reports and dashboards to track key usage metrics and communicate findings to stakeholders.
  • Collaborate with cross-functional teams to design and implement A/B tests to evaluate the impact of product changes on business outcomes.
  • Build models to predict user churn, identify at-risk subscribers, and forecast future user trends.
  • Work closely with product managers, marketers, and engineers to translate data insights into actionable recommendations.

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