In addition to possessing strong technical background of their 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 in analyzing and forecasting time series. Accompanying this broad set of responsibilities is exposure to many functional areas, as well as senior management, across Spotify.
What you'll do
- Support the production of Spotify's public-facing user growth estimates on a quarterly basis.
- Develop scalable solutions for forecasting Spotify's growth and work closely with Data Engineering to put your solutions into practice.
- Consult with functional analytics teams tasked with building predictive frameworks for their discrete business units.
- Visualize time series data in intuitive ways for a non-technical audience.
- Contribute to a machine learning framework to measure and predict Spotify user lifetime value metrics.
- Support Finance leadership with research on key business initiatives and challenges.
Who you are
- Degree in Computer Science/Engineering, Mathematics, Statistics, Economics, Econometrics, or another quantitative field.
- Minimum 3 (5+ preferred) years of relevant experience, particularly in forecasting time series using Python, SQL, Scala, and/or R.
- Experience with feature engineering for machine learning models.
- Knowledge of Google BigQuery and Java/Scala is a plus.
- Comfort operating independently in a fast-paced work environment.
We believe that everyone should enjoy their job, so we live by a work hard, play hard ethos. Spotify is a positive, fun, high-energy work environment that you've always wanted to be part of!