Smart Pricer Berlin vor 2 Monaten

Fullstack Data Scientist

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Das ist der Job

Company Description Airlines earn millions in additional revenue each year using dynamic pricing.

Darum lohnt es sich

Building upon our experience from working at airlines (Lufthansa and Air Berlin) and consulting (McKinsey) companies, Smart Pricer team is the leading Berlin start-up in the field of dynamic price optimization for sports, cinema and entertainment.

By being a part of our team you will work closely with our data science team on developing new pricing concepts and running simulations for customers such as Hertha BSC, UCI Kinowelt or Odeon UK.

Job Description WHAT WILL YOU DO? · Develop predictive models to forecast the demand for soccer matches, theater shows and concerts · Use live demand data to simulate the impact of price changes on the performance · Be responsible for every development step: Starting with the idea all the way to production · Assist the development of the Smart Pricer service to become the leading pricing tool for sports, concerts and theaters in Europe Qualifications WHAT BACKGROUND DO YOU NEED? · A degree in the field of computer science, similar disciplines or equivalent practical experience · Excellent skills in at least one general purpose programming language (Ruby, Python, Go, Java, ...) · Experience in data analysis, predictive model development and operating analytic services in a distributed system. · Hands-on knowledge on using common big data related technology (Kafka, Cassandra, Spark, Hadoop, …) WHO YOU ARE? · A tinkerer, who seeks to explore new things and solve problems · Experienced and always comfortable facing new challenges · Interested in applying machine learning to pragmatically solve business problems Additional Information WHAT CAN WE OFFER? · The opportunity to work with cutting-edge technology and directly impact innovative products · An open-minded team always looking for new ideas and solutions · A fast-paced work environment with flexible working hours Sports clubs and cinema operators are only beginning to consider actual bookings, weather, google searches and website clicks in their demand prediction and pricing.

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