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Senior Data Scientist (Finance)
Spotify
New York, NY, United States
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We seek an outstanding Sr. Data Scientist to join our Finance Analytics team in New York. This individual will be responsible for developing enterprise-grade predictive models to precisely estimate Spotify’s future user growth and content consumption among a multitude of dimensions. The output of your models will contextualize business performance for both internal and external stakeholders. Above all, you will be at the nexus of data science and business at one of the most innovative companies in the world.
In addition to possessing strong technical background of his/her own, the ideal candidate will be a natural communicator who is able to explain complex statistical frameworks to business and engineering teams in both New York and Stockholm. We also have a strong preference for candidates with experience forecasting growth at a public company. Accompanying this broad set of responsibilities is exposure to many functional areas, as well as senior management, across Spotify.
What You'll Do
• Lead the process of designing scalable solutions for forecasting Spotify’s growth and work closely with Data Engineering to put your solutions into practice.
• Serve as a consultant to functional analytical teams tasked with building predictive frameworks for their discrete business units.
• Provide ongoing project management and analytical support for the FP&A and Investor Relations teams.
• Drive transparency and operationalize service levels between the FP&A and Business Intelligence teams related to Big Data engineering support.
• Support ad hoc requests for data analysis from Finance leadership.
Who You Are
• Graduate level degree in Economics, Mathematics, Statistics, Computer Science, or another quantitative field.
• 5+ years of relevant experience, preferably at a publicly traded technology firm.
• Extensive experience manipulating and analyzing complex data with SQL, Python, and R. Knowledge of Google BigQuery is a plus.
• Basic familiarity with batch and real-time data processing frameworks like Crunch, Scalding, Storm, Kafka, or Spark.
• A strong understanding of dimensional warehouse data models.
• Comfort operating independently in a fast-paced work environment.
We are proud to foster a workplace free from discrimination. We strongly believe that diversity of experience, perspectives, and background will lead to a better environment for our employees and a better product for our users and our creators. This is something we value deeply and we encourage everyone to come be a part of changing the way the world listens to music.