Data Science Manager, Global On-Platform Marketing
New York, NY
We are looking for a Data Science Manager to join the Global On-Platform Marketing team at Spotify. You will lead a team of data scientists that support our owned-channel campaigns & infrastructure, providing key inputs that shape future direction and channel strategy. The manager will also define critical metrics, report on business impacts, and collaborate with cross-functional teams to enhance data-driven decision-making within the organization.
The Global On-Platform Marketing team is part of Spotify's Global Marketing & Partnerships organization. You'll play a crucial role in how we communicate with and delight our 625M+ users around the globe. At your fingertips, you'll have access to all of the data Spotify has to offer, and the opportunity to be creative with how you use it to derive insights and strategies. Above all, your work will impact the way the world experiences audio!
The Global On-Platform Marketing team is part of Spotify's Global Marketing & Partnerships organization. You'll play a crucial role in how we communicate with and delight our 625M+ users around the globe. At your fingertips, you'll have access to all of the data Spotify has to offer, and the opportunity to be creative with how you use it to derive insights and strategies. Above all, your work will impact the way the world experiences audio!
What You'll Do
- Manage and mentor a team of data scientists.
- Collaborate to define the team's long-term roadmap in alignment with marketing priorities.
- Direct pipelining and data infrastructure work.
- Deliver thoughtful analysis and insights around on-platform marketing campaigns
- Present your findings to marketing & xfn partners
- Design and implement comprehensive tests, making sure that we track all relevant metrics and that we're learning at every step along the way
- Create and communicate thoughtful recommendations that improve the impact & effectiveness of our marketing messages
- Work closely with our Marketing & Consumer Insights team to connect off-platform data & insights with our 1st party campaign data
Who You Are
- Bachelor's degree in Economics, Statistics, Mathematics, Engineering or equivalent.
- 5+ years of experience in Data Analytics or related occupation.
- 2+ years of experience in people management within data science.
- You are curious and not afraid of exploring new domains; you enjoy partnering with others to define and develop new opportunities
- You are a natural communicator; you focus just as much on how you deliver your findings, as you do on the technical craft of uncovering new insights
- Experience with complex data analysis using SQL and Python.
- Experience with experimentation methods such as A/B testing and RCTs.
- Proficiency in data visualization tools like Tableau.
- Ability to communicate data analytics to a broad range of stakeholders.
- Experience in architecting and scheduling data pipelines.
- Comfortable working on a globally distributed team
- Machine learning experience including forecasting or feature engineering is a plus
- Relevant experience in a consumer tech/product company is a plus
Where You'll Be
- You'll be based in NYC, with the option to work from the office or fully remote
- Working hours? You will operate within the EST time zone for collaboration
Job Profile
Regions
Countries
Must operate in EST Option for office or fully remote
Benefits/Perks401(k) Health insurance Paid holidays Paid parental leave Paid Sick Leave Paid Time Off Sick Leave
Tasks- Analyze marketing campaigns
- Connect data insights
- Data infrastructure
- Define roadmap
- Manage team
- Present findings
- Recommend improvements
A/B Testing Data analysis Data & Analytics Data Pipelines Data Science Data Visualization Feature Engineering Forecasting Machine Learning Python RCTs SQL Tableau
Experience5 years
EducationBachelor's degree Economics Engineering Mathematics Statistics
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9
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