Working Student Data Science (M/F/D) // Future Demand

Future Demand | Berlin, Germany

Date listed

1 month ago

Employment Type

Full time

Your responsibilities

  • Extract and combine data from a wide range of sources. Your main work will be to help our team to ensure data quality at all stages of the data pipeline.
  • Help to build and evaluate machine learning algorithms for predicting ticket sales and other meaningful target variables.
  • Analyze the behaviour of customers by using unsupervised learning techniques as well as visualizations.
  • You are closely involved in the entire development of our SaaS platform
Your qualifications and skills
  • Experience in using statistical tools like Pandas, Numpy and Scikit-Learn
  • You have a proven track record in coding with at least one scripting language (preferable Python).
  • You have a solid understanding of machine learning algorithms and hands-on experience working in data-based projects.
  • Basic knowledge of relational databases and SQL
  • A solid mathematical and statistical foundation
  • Passion for learning new technologies and concepts
Why us:
  • We offer an exciting environment at the interface between IT and Live-Entertainment and Sports as part of an ambitious, international and results-driven team in a young startup
  • Varied tasks with a wide range of great opportunities
  • Flexible working hours
  • Benefits package includes e.g.
    • Person professional development budget
    • Highly subsidised public transport work ticket
    • Free Urban Sports Club membership
    • and more…
  • Modern office in the heart of Kreuzkölln with all the usual perks
About us: We predict and create demand for the live-entertainment industry Using machine learning future demand develops a SaaS tool which enables companies both in the entertainment and sports sector to use insights from ticketing and external data from various sources to gain a deep understanding of their customers, predict attendance and sell more tickets via tailored marketing campaigns.

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