1 day ago

Data Scientist - Podcast Monetization

Spotify

On Site
Full Time
$135,121
New York, NY

Job Overview

Job TitleData Scientist - Podcast Monetization
Job TypeFull Time
CategoryCommerce
Experience5 Years
DegreeMaster
Offered Salary$135,121
LocationNew York, NY

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Job Description

About the Role

The Spotify Podcast R&D team consists of Data Scientists, Analytics Engineers and User Researchers dedicated to improving the experience of podcasts for both creators and users of the platform. This role will support our Product team in evaluating the performance of exciting features from Spotify for Creators like Podcast Comments, Creator Analytics, and the Spotify Partner Program.

What You'll Do

  • Develop research questions and undertake data exploration to understand creator monetization, and where we can develop our products to bring greater value to creators.
  • Work closely with cross-functional teams of data scientists, researchers, product owners, engineers, designers, marketers, and others across the company to develop and improve monetization tools for creators.
  • Define, evaluate, dashboard, and monitor metrics, understanding the root causes of changes.
  • Communicate insights and recommendations to collaborators across Spotify to build out our product strategy.
  • Maintain a culture of rigor and data-informed decision-making to drive tangible business impact.
  • Contribute to the development of the Insights function and the wider analytics community at Spotify.

Who You Are

  • Demonstrated ability in a similar Data Scientist - Podcast Monetization role.
  • Degree in data science, computer science, statistics, economics, mathematics, or a similar quantitative field.
  • Deeply curious; interested in the current and future creator ecosystem.
  • You have experience with product analytics, including crafting success metrics, performing exploratory analysis and presenting findings with clear product recommendations or implications.
  • You have hands-on experience synthesizing insights from data using tools such as Python, DBT, BigQuery, SQL, Tableau.
  • Strong communication skills and value building strong relationships with colleagues and partners as well as the ability to explain sophisticated topics in straightforward terms.
  • You’re a compelling storyteller who can communicate in succinct and inspiring ways to audiences with varied data science experience to influence product or feature decisions.

Where You'll Be

This Data Scientist - Podcast Monetization role is based in our New York office. We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.

Key skills/competency

  • Data Science
  • Podcast Monetization
  • Product Analytics
  • SQL
  • Python
  • BigQuery
  • DBT
  • Tableau
  • Creator Economy
  • Cross-functional Collaboration

Tags:

Data Scientist
Podcast Monetization
Product Analytics
Creator Economy
Data Exploration
Metrics Definition
Business Impact
SQL
Python
BigQuery
DBT
Tableau
Data Storytelling
Cross-functional Collaboration
Analytics

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How to Get Hired at Spotify

  • Research Spotify's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor to understand their innovative and creator-focused environment.
  • Tailor your resume: Customize your resume to highlight experience in data science, product analytics, and monetization, specifically referencing Python, SQL, BigQuery, DBT, and Tableau skills relevant to Spotify's Data Scientist - Podcast Monetization role.
  • Showcase data storytelling: Prepare examples of how you've communicated complex data insights and influenced product decisions, demonstrating strong storytelling abilities for diverse audiences at Spotify.
  • Understand the creator economy: Articulate your passion and insights into the podcast and creator ecosystem, showing curiosity and understanding of Spotify's strategic direction in monetization.
  • Prepare for technical interviews: Practice SQL queries, Python data manipulation, and product analytics case studies, focusing on how you would approach monetization challenges specific to Spotify's platform.

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