Data Scientist (Remote)

Role: Data Scientist (2 Openings)

Rate: €400 per day

Contract Type: 3-month rolling contract (project expected to run for 18–24 months)

Work Arrangement: Fully remote

Interview Rounds: Two stages

Project Overview:

You'll be contributing to a large-scale energy trading and risk management (ETRM) initiative. The focus is on developing and deploying advanced machine learning solutions to support forecasting, analytics, and automation goals.

Essential Skills & Experience:

• Strong background in time-series forecasting using models like Prophet, ARIMA, SARIMA, XGBoost, Random Forest, ElasticNet, Ridge, Lasso, and Linear Regression.
• Hands-on experience with Python machine learning libraries including scikit-learn, sktime, and darts.
• In-depth understanding of time-series feature engineering, including creation of lag variables, rolling window metrics, Fourier transforms, and approaches to seasonality.
• Capable of optimizing and fine-tuning deployed predictive models for enhanced accuracy and stability.
• Practical experience using Azure Machine Learning SDK (both v1 and v2), particularly for:
• Managing assets (data, models, environments)
• Creating and debugging ML pipelines for feature engineering, training, and deployment
• Scheduling jobs and deploying endpoints

Additional Skills (Nice to Have):

• Familiarity with unsupervised learning techniques such as K-Means clustering.
• Experience designing and building scalable data solutions using cloud-native tools like Azure Data Factory, Azure Databricks, Azure Data Lake, and Azure Key Vault.
• Ability to create and maintain resilient data pipelines for ETL processes, logging, and transformation using Azure Data Factory.
• Skilled in large-scale data manipulation and analysis using PySpark and Python.
• Collaborates effectively with product and engineering teams to translate business goals into data-driven solutions.
• Experience setting up CI/CD pipelines within Azure DevOps for machine learning and data infrastructure.
• Committed to data engineering best practices including governance, security, and performance tuning.
• Stays updated with modern data technologies and methodologies, constantly pushing to evolve existing frameworks.

Apply now or reach out to Odin Lawton.