AI, BI and Data Analytics Solutions Engineer (m / f)

Experis; Merzig; Hybrid; EUR 65.000 - 85.000; Vollzeit

Zusammenfassung

A leading IT recruitment agency is seeking a Senior AI, BI and Data Analytics Solutions Engineer to develop data-centric solutions. Candidates should have a Bachelor's degree and experience in Data Science and AI techniques, including proficiency in programming languages like Python. This role offers a chance to work with experts and the possibility of remote work.

Leistungen

Working alongside recognized experts

Possibility of working partly from home

Excellent training

Qualifikationen

• Strong analytical skills and experience in data-driven decision-making.
• Deep knowledge of Data Science and AI techniques.
• Proficient in programming for analytics using Python or R.

Aufgaben

• Develop prototypes and solutions using Data Analytics and AI.
• Provide training and support for AI and Data Analytics tasks.
• Implement MLOps practices for automated testing and QA.

Kenntnisse

Analytical skills

Statistical analysis

Machine learning

Python

Data analysis techniques

Ausbildung

Bachelor's degree in Computer Science or related field

Tools

PowerBI

Oracle

Airflow

MongoDB

Jobbeschreibung

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

• Develop prototypes and data-centric solutions for various users using Data Analytics (DA) and Artificial Intelligence (AI).
• 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).
• Prepare architectural outputs related to AI and DA (Reference Data Architecture, Data Platforms).
• Collect and analyze business requirements.
• Perform technical analyses and create specifications for AI and DA solutions.
• Conduct exploratory data analyses to identify, interpret, and analyze patterns and trends in complex datasets for diagnosis and prediction.
• 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.
• Implement MLOps practices, including automated testing and quality assurance.
• Define and document training and support procedures.
• Maintain DA and AI products, including troubleshooting, bug fixing, performance analysis, and technical migrations.
• Architect, design, deploy, and manage components of data platforms.
• Integrate and reuse COTS, SaaS, PaaS, and SaaS solutions.
• Design and implement data protection and security measures.
• Define testing strategies, design tests, and conduct testing.
• Establish best practices and standards.
• Conduct technology watch, evaluate technologies, and contribute to platform definition and strategy documents.

Your profile

• Bachelor's degree in Computer Science, Information Technology, or any related field.
• Business analysis skills.
• Strong analytical skills, capable of identifying patterns and gaps while exploring data.
• Deep knowledge of statistical analysis and data-driven decision-making.
• Extensive experience with Data Science and AI techniques, particularly in prediction, machine learning, and Generative AI.
• Proficient in programming languages for data analytics and AI (e.g., Python, R) and frameworks (e.g., .NET AI, SpringAI).
• Experienced in machine learning algorithms (e.g., ANN, random forest) and deep learning frameworks.
• Skilled in developing reusable AI models (e.g., huggingface) and Generative AI APIs (e.g., OpenAI).
• Experienced in the industrialization of DA and AI solutions.
• Knowledgeable about MLOps tools, testing, and quality assurance.
• Proficient with visualization tools (e.g., PowerBI).
• Knowledgeable in SQL (e.g., Oracle, SQL Server) and No-SQL databases (e.g., MongoDB, Neo4j).
• Experienced with orchestration tools (e.g., Airflow) and ETL tools (e.g., DBT, SSIS).
• Familiar with search engines (e.g., ElasticSearch, SOLR).
• Knowledgeable in data modeling for data lakes and data warehouses.
• Experienced with cloud environments and containerization.
• English fluency. Any other language would be an asset.

Client’s offer

• Working alongside recognized experts.
• Possibility of working partly from home.
• An excellent training and a reputed expertise