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À propos
You will work with a team of data engineers and scientists who use data and apply cutting statistical machine learning models to build forecasting models for different energy markets. The entire Data team works collaboratively and is a strong partner for teams across the company. You will get to meet and learn from diverse and talented colleagues. Specific Responsibilities Analyze energy time series and summarize the statistical properties of energy signals Build predictive models and forecast signals for day?ahead consumption data Evaluate the performance and compare the results with existing models Deploy the best model and document the result of this research
Business Skills
Excellent verbal, written, and interpersonal communication skills Strong understanding of the product development lifecycles Strong understanding of software development, testing and integration methodologies Personal effectiveness/credibility Strong problem solving and analysis skills
Technical Skills
Proficiency with Python or R, SQL and familiarity with working in big data environments (2 years minimum) At least 2+ years of experience of deploying machine learning models and frameworks in production At least 3 years of experience with supervised and unsupervised machine learning models (regressions, gradient boosted methods, SVMs, random forests, clustering) Familiar with Python packages such as Pandas, Sklearn, NumPy, etc. Deep learning (CNN, RNN, LSTM) and framework libraries (e.g., Keras, TensorFlow, PyTorch) and graph neural networks Evaluation and hypothesis testing At least 3 years of experience with cloud computing platforms such as AWS, Azure (preferably AWS) Experience with standard CI/CD build and deployment pipeline technologies At least 2 years of experience in distributed computing frameworks such as Spark or PySpark
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Compétences linguistiques
- English
Avis aux utilisateurs
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