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

Experis; Konz; Hybrid; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

A leading company is seeking a Senior AI, BI and Data Analytics Solutions Engineer to develop data-centric solutions and enhance AI initiatives. The position requires extensive experience in data science techniques, programming for analytics, and excellent analytical skills. You'll work with a team of experts and have the flexibility of partial remote work, alongside opportunities for professional training.

Leistungen

Possibility of working partly from home

Excellent training opportunities

Qualifikationen

• Bachelor's degree in a related field.
• Deep knowledge of statistical analysis.
• Experience with Data Science techniques.

Aufgaben

• Develop prototypes and solutions using Data Analytics and AI.
• Guide and train others on AI and DA tasks.
• Conduct exploratory data analyses on complex datasets.

Kenntnisse

Analytical Skills

Statistical Analysis

Python

Machine Learning

Generative AI

SQL

No-SQL Databases

Cloud Environments

Data Protection

Ausbildung

Bachelor's degree in Computer Science

Tools

PowerBI

Airflow

ETL Tools

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