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Senior Data Analyst and Artificial Intelligence Specialist

il y a 3 semaines

Luxembourg, Luxembourg beBee Careers Temps plein
About the Role

As a seasoned professional in data analytics and artificial intelligence, we are seeking an expert to lead our team in developing innovative solutions.

The ideal candidate will have a deep understanding of machine learning algorithms, statistical analysis, and data-driven decision-making. Additionally, experience with programming languages such as Python and R, as well as frameworks like .NET AI and SpringAI, is essential.

We are looking for someone who can design, model, develop, manage, and review end-to-end data and AI products, including data preparation, feature engineering, model selection and training, visualization, deployment, monitoring, and maintenance.

A strong analytical mindset, business analysis skills, and the ability to identify patterns and gaps while exploring data are also key requirements.

Responsibilities
  • Data Analysis and Artificial Intelligence: Develop prototypes and data-centric solutions using Data Analytics (DA) and Artificial Intelligence (AI).
  • Guidance and Support: Provide guidance, support, and training for AI and DA tasks for both technical and non-technical audiences.
  • Architectural Outputs: Prepare architectural outputs related to AI and DA, including reference data architecture and data platforms.
  • Business Requirements: Collect and analyze business requirements.
  • Technical Analysis: Perform technical analyses and create specifications for AI and DA solutions.
  • Exploratory Data Analysis: Conduct exploratory data analyses to identify, interpret, and analyze patterns and trends in complex datasets.
  • Product Development: Design, model, develop, manage, and review end-to-end DA and AI products.
  • MLOps Practices: Implement MLOps practices, including automated testing and quality assurance.
  • Training and Support: Define and document training and support procedures.
  • Product Maintenance: Maintain DA and AI products, including troubleshooting, bug fixing, performance analysis, and technical migrations.
  • Data Platforms: Architect, design, deploy, and manage components of data platforms.
  • Integration: Integrate and reuse COTS, SaaS, PaaS, and SaaS solutions.
  • Data Security: Design and implement data protection and security measures.
  • Testing Strategies: Define testing strategies, design tests, and conduct testing.
  • Best Practices: Establish best practices and standards.
  • Technology Watch: Conduct technology watch, evaluate technologies, and contribute to platform definition and strategy documents.
Requirements
  • Bachelor's Degree: Bachelor's degree in Computer Science, Information Technology, or any related field.
  • Business Analysis Skills: Business analysis skills.
  • Analytical Skills: Strong analytical skills, capable of identifying patterns and gaps while exploring data.
  • Statistical Analysis: Deep knowledge of statistical analysis and data-driven decision-making.
  • Data Science and AI Techniques: Extensive experience with Data Science and AI techniques, particularly in prediction, machine learning, and Generative AI.
  • Programming Languages: Proficient in programming languages for data analytics and AI, e.g., Python, R, .NET AI, SpringAI.
  • Machine Learning Algorithms: Experienced in machine learning algorithms, e.g., ANN, random forest.
  • Deep Learning Frameworks: Skilled in developing reusable AI models, e.g., huggingface, and Generative AI APIs, e.g., OpenAI.
  • MLOps Tools: Knowledgeable about MLOps tools, testing, and quality assurance.
  • Visualization Tools: Proficient with visualization tools, e.g., PowerBI.
  • Databases: Knowledgeable in SQL, e.g., Oracle, SQL Server, and No-SQL databases, e.g., MongoDB, Neo4j.
  • Orchestration Tools: Experienced with orchestration tools, e.g., Airflow, and ETL tools, e.g., DBT, SSIS.
  • Search Engines: Familiar with search engines, e.g., ElasticSearch, SOLR.
  • Data Modeling: Knowledgeable in data modeling for data lakes and data warehouses.
  • Cloud Environments: Experienced with cloud environments and containerization.
  • Language Skills: English fluency; any other language would be an asset.
About the Opportunity
  • Collaborative Environment: Work alongside recognized experts.
  • Remote Work Option: Possibility of working partly from home.
  • Training and Expertise: An excellent training and a reputed expertise.