Synthetic Data
il y a 5 jours
Department: IT - Business Solutions | Location: Merl-Luxembourg | Contract: Internship 6 months
About Us
At Creos, we play a central role in shaping the energy future of Luxembourg. As a Distribution System Operator (DSO), we manage and operate the country's electricity and gas networks — ensuring reliable delivery in a landscape increasingly driven by digitalization, decentralization, and decarbonization.
To support this transformation, our IT Business Solutions department contributes to a company-wide Data & AI Initiative, focused on leveraging data science, machine learning, and AI to enable smarter and safer energy operations.
Your Mission
As a Synthetic Data & Analytics Intern, you'll work at the intersection of data science, analytics, and privacy engineering. Your mission: help design, generate, and evaluate synthetic datasets that enable realistic, GDPR-safe testing and analytics in our energy systems environment.
You'll collaborate with Solution Architects, functional analysts, and IT stakeholders to:
- Build and evaluate synthetic data generation models
- Ensure data quality, consistency, and privacy compliance
- Translate technical findings into clear business insights
- What You'll Do
- Collect, clean, and preprocess structured datasets from internal systems
- Apply data normalization, missing-value handling, and data quality checks
- Perform exploratory data analysis (EDA) to uncover trends and correlations
- Compare synthetic vs. real datasets to assess representativeness and performance
- Document and visualize results through reports and dashboards
- Work closely with business and IT teams to ensure compliance and alignment with corporate goals
Your profile
- Pursuing a Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field
- Strong skills in Python (pandas, NumPy, matplotlib, etc.) for data manipulation and visualization
- Basic understanding of machine learning and deep learning (e.g., regression, classification, generative models)
- Knowledge of data profiling, statistical analysis, and data pipeline concepts
- Familiarity with synthetic data generation tools or cloud/MLOps environments (AWS, SageMaker) is a plus
- Excellent communication skills — you can explain technical findings to non-technical audiences
- Analytical, proactive, and comfortable working in cross-functional teams
What We Offer
- A hands-on experience in synthetic data design and analytics within a real-world energy environment
- The opportunity to contribute to safe, GDPR-compliant data innovation
- Exposure to cutting-edge AI and data engineering practices
- Guidance from experienced data scientists and solution architects
- The chance to connect your internship to a thesis or research project
- A meaningful role in supporting Luxembourg's energy transition
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