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Working Student Data Science (m/f/d)

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.

future demand’s platform helps companies in the entertainment and sports sector to use insights from ticketing and external data to predict attendance and sell more tickets for low attendance events.

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