Synthetic Data & Analytics Intern - Business Solutions (m/f/n)

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


Segment de l’offre d’emploi: Pipeline, Statistics, Engineer, Intern, Analytics, Energy, Data, Engineering, Entry Level, Management