Working Student

Vor 2 Tagen

München, Deutschland Siemens Vollzeit

**Mode of Employment**: Limited; max. 20 h / week

**Develop what will be important tomorrow.**

How will we travel, communicate, and use energy in the world of tomorrow? Work on the right answers with us. We are looking for bright minds - thinkers with a passion for practical matters. In short, people who can turn their questions and ours into exciting new discoveries. When you join our team as one of our working students, you will find many opportunities to get involved. Seize the chance to be part of our global network, make key contacts, and get your career as well as your personal life on the best track. Our teams are curious to meet you.

We at the Environmental Protection Data Analytics team are seeking a motivated and skilled student to support the development of Machine Learning (ML) models for data analyses. In this role, the student will have the opportunity to work on various tasks related to data harvesting, ML model development, and analysis to support environmental protection initiatives

**Change the future with us.**
- Data Harvesting: Develop approaches to extract and gather external data from public APIs and internal Environmental Management systems. Identify relevant data sources and implement data extraction techniques.
- ML Model Development: Develop and train ML models using the harvested data. Perform feature engineering, model selection, parameter tuning, and evaluation.

**What you need to make real what matters.**
- You are enrolled in your Bachelors or Masters studies with a background in Computer Science. Experience with Information Engineering / data science topics will be a plus.
- You are proficient in working with APIs and extracting data from public sources. Knowledge of data manipulation techniques and tools, such as Python libraries: Requests or BeautifulSoup.
- You have strong programming skills, particularly in Python. Experience with ML frameworks and libraries, such as scikit-learn or TensorFlow will be a plus. Familiarity with feature engineering techniques and model evaluation metrics.
- You are proficient in data analysis and visualization using tools like Pandas, NumPy, and Matplotlib. Knowledge of sentiment analysis techniques and NLP (Natural Language Processing) libraries, such as NLTK, spaCy, Gensim, VADER etc. Understanding of language models and frameworks like BERT or GPT, and familiarity with the OpenAI API will be a plus.
- You have very good language skills, either in English or German (C1)

**We’ve got quite a lot to offer. How about you?**

if you wish to find out more about Siemens before applying.

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