Contract Duration : 1 Year and can be extended
Languages Required : English, German (Nice to have)
Remote / Onsite / Hybrid : Hybrid (23 days every week)
Years of Experience Needed : 10 years
ETRM Data Scientist
Experience : 7 years
Job Description :
* Education Requirements :
Master’s degree in Mathematics, Statistics, Data Science, or related fields is mandatory.
* A Ph.D. in Mathematics, Statistics, Data Science, or similar areas is preferred but not mandatory.
* Mandatory Skills :
Data Science :
* Extensive experience in timeseries forecasting, predictive modelling, and deep learning.
* Proficient in designing reusable and scalable machine learning systems.
* Proficiency in implementing techniques such as ARIMA, LSTM, Prophet, Linear Regression, and Random Forest to ensure accurate forecasting and insights.
* Strong command of machine learning libraries including scikit-learn, XGBoost, Darts, TensorFlow, and PyTorch along with data manipulation tools like Pandas and NumPy.
* Proven expertise in designing and implementing explicit ensemble techniques such as stacking, boosting, and bagging to improve model accuracy and robustness.
* Proven track record of analysing and optimizing performance of operational machine learning models to ensure long-term efficiency and reliability.
* Expertise in retraining and finetuning models based on evolving data trends and business requirements.
* MLOps Implementation :
Proficiency in leveraging Python-based MLOps frameworks for automating machine learning pipelines including model deployment, monitoring, and periodic retraining.
* Advanced experience in using the Azure Machine Learning Python SDK to design and implement parallel model training workflows incorporating distributed computing, parallel job, and efficient handling of large-scale datasets in managed cloud environments.
Strong experience in PySpark for scalable data processing and analytics.
* Azure Machine Learning : Managing parallel model training, deployment, and operationalization using the Python SDK.
* Azure Databricks : Collaborating on data engineering and analytics tasks using PySpark/Python.
* Azure Data Lake : Implementing scalable storage and processing solutions for large datasets.
* Preferred Skills :
KMeans Clustering : Experience in applying k-means clustering for data segmentation and pattern identification.
* Bottom-Up Forecasting: Skilled in creating granular bottom-up forecasting models for hierarchical insights.
* Azure Data Factory: Designing, orchestrating, and managing pipelines for seamless data integration and processing.
* Knowledge of power trading concepts.
* Generative AI (GenAI): Experience in applying generative AI models such as GPT or similar frameworks.
Key Skills:
Apache Hive, S3, Hadoop, Redshift, Spark, AWS, Apache Pig, NoSQL, Big Data, Data Warehouse, Kafka, Scala
Employment Type : Full Time
Vacancy : 1
Data Scientist • Essen, North Rhine-Westphalia, Germany
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