Integrate an international data analytics team with diverse backgrounds, utilizing state-of-art data analytics tools and methodologies; Collaborate and interact regularly with internal customers and other data teams across Siemens as a consultant and enabler; Implement and develop solutions for business uses cases applying AI/ML techniques and frameworks, including LLM models; Ensure compliance with Siemens security and privacy standards for data handling and model deployment
Requirements:
Curiosity and willingness to learn new and upcoming technologies; Bachelor/Master’s (or equivalent) in Computer Science Engineering, Statistics or related field; Background in data science including statistical analysis and modeling, data mining, machine learning, uncertainty analysis, time series forecasting, working with both structured and unstructured data; Strong problem-solving and analytical thinking skills; Knowledge and understanding of ML models, including LLM; Programming experience in Python and any Data Science & ML packages, such as: numpy, pandas, matplotlib, scikit-learn, TensorFlow, Keras, nltk, spacy, gensim; Knowledge and familiarity with SQL; Excellent oral and written English skills
Text:
Data Scientist Trainee (m/f/d) Integrate an international data analytics team with diverse backgrounds, utilizing state-of-art data analytics tools and methodologies; Collaborate and interact regularly with internal customers and other data teams across Siemens as a consultant and enabler; Implement and develop solutions for business uses cases applying AI/ML techniques and frameworks, including LLM models; Ensure compliance with Siemens security and privacy standards for data handling and model deployment Curiosity and willingness to learn new and upcoming technologies; Bachelor/Master’s (or equivalent) in Computer Science Engineering, Statistics or related field; Background in data science including statistical analysis and modeling, data mining, machine learning, uncertainty analysis, time series forecasting, working with both structured and unstructured data; Strong problem-solving and analytical thinking skills; Knowledge and understanding of ML models, including LLM; Programming experience in Python and any Data Science & ML packages, such as: numpy, pandas, matplotlib, scikit-learn, TensorFlow, Keras, nltk, spacy, gensim; Knowledge and familiarity with SQL; Excellent oral and written English skills
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