Experis IT Luxembourg is actively looking for a Senior AI, BI and Data Analytics Solutions Engineer (m/f) for one of its clients in Luxembourg.
Your responsibilities
1. Develop prototypes and data-centric solutions for various users using Data Analytics (DA) and Artificial Intelligence (AI).
2. Provide guidance, support, and training for AI and DA tasks for both technical and non-technical audiences (Modeling, Design, Architectural Reviews, AI initiatives, Standards, and Processes, Center of Expertise).
3. Prepare architectural outputs related to AI and DA (Reference Data Architecture, Data Platforms).
4. Collect and analyze business requirements.
5. Perform technical analyses and create specifications for AI and DA solutions.
6. Conduct exploratory data analyses to identify, interpret, and analyze patterns and trends in complex datasets for diagnosis and prediction.
7. Design, model, develop, manage, and review end-to-end DA and AI products, prototypes, and proof of concepts on both on-premise and cloud data platforms, including data preparation, feature engineering, model selection and training, visualization, deployment, monitoring, and maintenance.
8. Implement MLOps practices, including automated testing and quality assurance.
9. Define and document training and support procedures.
10. Maintain DA and AI products, including troubleshooting, bug fixing, performance analysis, and technical migrations.
11. Architect, design, deploy, and manage components of data platforms.
12. Integrate and reuse COTS, SaaS, PaaS, and SaaS solutions.
13. Design and implement data protection and security measures.
14. Define testing strategies, design tests, and conduct testing.
15. Establish best practices and standards.
16. Conduct technology watch, evaluate technologies, and contribute to platform definition and strategy documents.
Your profile
17. Bachelor's degree in Computer Science, Information Technology, or any related field.
18. Business analysis skills.
19. Strong analytical skills, capable of identifying patterns and gaps while exploring data.
20. Deep knowledge of statistical analysis and data-driven decision-making.
21. Extensive experience with Data Science and AI techniques, particularly in prediction, machine learning, and Generative AI.
22. Proficient in programming languages for data analytics and AI (e.g., Python, R) and frameworks (e.g., .NET AI, SpringAI).
23. Experienced in machine learning algorithms (e.g., ANN, random forest) and deep learning frameworks.
24. Skilled in developing reusable AI models (e.g., huggingface) and Generative AI APIs (e.g., OpenAI).
25. Experienced in the industrialization of DA and AI solutions.
26. Knowledgeable about MLOps tools, testing, and quality assurance.
27. Proficient with visualization tools (e.g., PowerBI).
28. Knowledgeable in SQL (e.g., Oracle, SQL Server) and No-SQL databases (e.g., MongoDB, Neo4j).
29. Experienced with orchestration tools (e.g., Airflow) and ETL tools (e.g., DBT, SSIS).
30. Familiar with search engines (e.g., ElasticSearch, SOLR).
31. Knowledgeable in data modeling for data lakes and data warehouses.
32. Experienced with cloud environments and containerization.
33. English fluency. Any other language would be an asset.
Client's offer
34. Working alongside recognized experts.
35. Possibility of working partly from home.
36. An excellent training and a reputed expertise