Beschreibung
Responsibilities:Process various sets of structured/unstructured data from internal and external sources in a variety of formats.
Program significant metrics and indicators with advanced analytical functions and machine learning in Python, Spark (PySpark), and Scala.
Solve classification, clustering, regression and prediction problems with state-of-the-art machine learning methods.
Handle imbalanced data sets and derive conclusions about data and model predictions from your expertise in statistics and machine learning estimators.
Implement data preparation methods including cleaning, pre-processing and verification of data integrity.
Derive meaningful features from prepared data and interpret their usefulness together with different machine learning models.
Develop new advanced algorithms for time series predictions, survival analysis, condition monitoring, state change detection, and asset optimization.
Perform explorative and ad-hoc data analysis, visualize results in an appealing manner and present the findings in clear statements to business partners.
Soft-Skills:
• Good team player, but great at independent work
• Solution oriented
• Analytical thinking
• Fluent in English. German considered as a plus
Skills and Experience:
Ph.D. or master degree in Computer Science, Mathematics, or related technical discipline.
Minimum 2 years working experience as a data scientist.
Extensive knowledge in statistics, machine learning (both theory and application, especially decision-trees, ensemble methods), time series and survival analysis, and data mining.
Expertise in at least one Python machine learning library, e.g. scikit-learn, h2o etc.
Track record of implementing advanced data analytics in Hadoop using Spark, Python, HDFS, Hive, and HBase. Scala knowledge is a plus.
Experience with databases (e.g. SQL) is useful.