Data Science Werkstudent/ Working Student
vor 6 Monaten
**Join Our Team**
We have successfully managed steady growth over the past 9 years and want to continue our growth curve in the EU und US. We embrace innovation and are proud to have a dynamic, team focused culture.
We are an equal rights employer, with flat hierarchies and a focus on the team. Our values are team spirit, willingness to learn and constant improvement, honesty, trust, taking initiative and ownership, and last but not least having fun.
If this excites you as much as us then we would like to hear from you
Currently, we are looking to fill a vacancy for a
**Data Science Werkstudent/ Working Student (f/m/d)**
**possibility to combine the job with a Master thesis**
**What you should bring**:
- Strong experience in Python
- Good knowledge of statistics and probability theory
- Nice to have skills are: SQL, Pymc, Bayesian statistics, Marketing experience
- The ability to be both a analytical thinker and a problem-solver
- A collaborative, can-do attitude
- A keen eye for attention to detail
**Your Role**:
- Support the Analytics team in training, testing and improving of our machine learning models
- Help ensuring high reliability, efficiency and quality of model output
- Work within project teams of 2-3 people
**What can you further expect from us**:
- Competitive salary
- Flexible working hours
- Education budget
- Very international environment
- Being part in a highly motivated and outstanding talented team
**Want to join us? Send us your CV**
**Next steps in the hiring process are**:
(1) a small challenge,
(2) a video call,
(3) a personal interview at our office in Berlin,
and finally (4) signing the contract and **making math rock** ;-)
**Benefits**:
- Bonus scheme
- Free drinks
- Flexible working hours
**Job Types**: Part-time, Temporary, Internship
Contract length: 12 months
Pay: 1.080,00€ per month
Expected hours: 20 per week
**Education**:
- Bachelor's (preferred)
**Experience**:
- Python: 2 years (required)
- SQL: 1 year (preferred)
Work Location: In person
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