Data Scientist

von: SKAN AG | Ort: Allschwil
N: SKANAG

In this role, you should be highly analytical with a knack for coding, analysis, math, and statistics. You should be comfortable with in data visualization and programming and organization of data. Critical thinking and problem-solving skills are essential for interpreting data. Capability to work in a diverse environment from assembly hall to microbial lab will be expected. We also want to see a passion for machine-learning and research.
Your goal will be to help our research analyze trends in big data sets coming from experiments with multiple sensor setups to make better conclusions and decisions.
 

Responsibilities

  • Identify valuable data sources and automate collection processes
  • Organize and manage the research team database 
  • Undertake preprocessing of structured and unstructured data
  • Analyze large amounts of data to discover trends and patterns
  • Build predictive models and machine-learning algorithms
  • Combine models through ensemble modeling
  • Present information using data visualization techniques
  • Propose solutions and strategies to research challenges
  • Collaborate with our product development team

 

Hardskills

  • MSc in Computer Science, Engineering, or relevant field; graduate degree in Data Science or another quantitative field is preferred
  • Proven experience as a Data Scientist 
  • Experience in data mining
  • Understanding of machine-learning and operations research
  • Knowledge of R, SQL and Python; familiarity with JSL, Scala, Java or C++ is an asset
  • Business fluent in English, knowledge of German is an advantage

 

Softskills

  • Analytical mind 
  • Strong math skills (e.g., statistics, algebra)
  • Problem-solving attitude
  • Excellent communication and presentation skills

 

We offer you

  • An open and collegial corporate culture
  • Freedom for ideas
  • Participation in sports and leisure activities
  • Promotion through further training, especially at our SKAN Academy
  • Intensive and job-oriented introduction
  • Short decision-making paths and flat hierarchies
  • Open communication policy
  • 5 weeks holidays and the possibility of further holidays

 

For questions please contact Joel Streit

 

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