StartUs GmbH
Sr Data Scientist
StartUs GmbH, New York, New York, us, 10261
We seek an outstanding Sr. Data Scientist to join our Forecasting team in New York.
This individual will be responsible for developing enterprise-grade predictive models to estimate Spotify’s future user growth and content consumption. The output of your models will serve as the basis for the company’s financial forecast as well as provide context for business performance to 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 forecasting experience at a public company. Accompanying this broad set of responsibilities is exposure to many functional areas, as well as senior management, across Spotify.
THE MISSION SHOULD WE CHOOSE YOU TO ACCEPT IT
Support the production of Spotify’s public guidance on a quarterly basis.
Own and 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.
Design novel frameworks for detecting anomalies in Spotify’s data and put them into production.
Support Finance leadership with research on key business initiatives and challenges
WHAT YOU NEED TO GET AN AUDITION
Degree in Economics, Mathematics, Statistics, Computer Science, or another quantitative field.
8+ years of relevant experience, preferably at a publicly traded technology firm.
Extensive experience manipulating and analyzing complex data with SQL, Python and/or R. Knowledge of Google BigQuery and Scala is a plus.
Familiarity with big data processing frameworks like Hadoop or Spark is a plus.
Comfort operating independently in a fast-paced work environment.
This individual will be responsible for developing enterprise-grade predictive models to estimate Spotify’s future user growth and content consumption. The output of your models will serve as the basis for the company’s financial forecast as well as provide context for business performance to 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 forecasting experience at a public company. Accompanying this broad set of responsibilities is exposure to many functional areas, as well as senior management, across Spotify.
THE MISSION SHOULD WE CHOOSE YOU TO ACCEPT IT
Support the production of Spotify’s public guidance on a quarterly basis.
Own and 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.
Design novel frameworks for detecting anomalies in Spotify’s data and put them into production.
Support Finance leadership with research on key business initiatives and challenges
WHAT YOU NEED TO GET AN AUDITION
Degree in Economics, Mathematics, Statistics, Computer Science, or another quantitative field.
8+ years of relevant experience, preferably at a publicly traded technology firm.
Extensive experience manipulating and analyzing complex data with SQL, Python and/or R. Knowledge of Google BigQuery and Scala is a plus.
Familiarity with big data processing frameworks like Hadoop or Spark is a plus.
Comfort operating independently in a fast-paced work environment.