Data Science Engineernew

TN Germany; Kiel; Vor Ort; EUR 60.000 - 100.000; Vollzeit

Zusammenfassung

Join a forward-thinking company as a Data Science Engineer, where you will play a pivotal role in bridging data science and engineering. This position involves designing and maintaining scalable data pipelines, implementing machine learning models, and utilizing advanced data analysis techniques. You will collaborate with cross-functional teams to develop innovative data-driven solutions that enhance business objectives. If you are passionate about data science and eager to contribute to cutting-edge projects in a dynamic environment, this opportunity is perfect for you.

Qualifikationen

• 3+ years of experience in Data Science or Machine Learning roles.
• Proficiency in Python, R, and data processing frameworks.

Aufgaben

• Design and maintain scalable data pipelines for large data volumes.
• Build and deploy machine learning models into production environments.

Kenntnisse

Python

R

Machine Learning

Data Analysis

NLP

SQL

Problem-solving

Communication

Ausbildung

Bachelor's degree in Computer Science

Master's degree in Data Science

Tools

Hadoop

Spark

AWS

Azure

GCP

Docker

Kubernetes

Git

Matplotlib

Tableau

Jobbeschreibung

A Data Science Engineer typically plays a crucial role in bridging the gap between data science and engineering. Their responsibilities revolve around leveraging data science techniques and technologies to build scalable, efficient, and reliable data-driven solutions.

Responsibilities

1. Collaborate with data scientists, software engineers, and stakeholders to understand data requirements and business objectives.
2. Design, develop, and maintain scalable data pipelines for ingesting, processing, and analyzing large volumes of data.
3. Implement data preprocessing, feature engineering, and data transformation techniques to prepare data for analysis and modeling.
4. Build and deploy machine learning models into production environments, ensuring scalability, efficiency, and reliability.
5. Develop software applications, libraries, and APIs for automating data processing, analysis, and visualization tasks.
6. Implement machine learning algorithms using programming languages such as Python and R to develop predictive models and data-driven solutions.
7. Conduct text analysis, including processing unstructured data and implementing NLP techniques and Large Language Models (LLMs).
8. Perform pattern analysis to identify trends and anomalies within datasets and predict future values using predictive modeling techniques.
9. Conduct exploratory data analysis (EDA) to extract insights and identify relationships within data.
10. Prepare data for analysis by cleaning, transforming, and engineering features to enhance model performance.
11. Demonstrate proficiency in data science technologies and concepts, including NLP, neural networks, computer vision, EDA, supervised and unsupervised learning, and predictive modeling.
12. Implement MLOps practices such as CI/CD on platforms like Kubernetes, Azure AKS, or cloud services like AWS, Azure, GCP.
13. Ensure code quality through reviews and support junior developers and students.
14. Engage in technical and non-technical communication with stakeholders.
15. Manage day-to-day MLOps tasks in the Data Science and Machine Learning domain.
16. Contribute to future AI applications, domains, and roadmaps.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• At least 3 years of experience in Data Science, Machine Learning, or Software Engineering roles.
• Proficiency in Python, R, Java, or Scala.
• Experience with data processing frameworks such as Hadoop, Spark, or Flink.
• Proficiency in NLP tools like NLTK, spaCy, BERT, and familiarity with LLMs such as GPT-3, BERT, XLNet.
• Experience with cloud platforms (AWS, Azure, GCP) and big data technologies.
• Knowledge of ML libraries like scikit-learn, TensorFlow, PyTorch, Keras.
• Experience with data visualization tools such as Matplotlib, Seaborn, Tableau.
• Understanding of MLOps practices, including model deployment and monitoring.
• Proficiency in SQL, Git, Docker, and Kubernetes.
• Excellent analytical, problem-solving, and communication skills.

Contact

If interested, please submit your application with an up-to-date CV, using the job title “Data Science Engineer” in the subject line. No cover letter is required.

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