DESCRIPTION OF THE TASKS:
- Collect business requirement and analyse advanced AI solutions or identify and assess relevant existing data mining, machine learning and business intelligence solution
- Specification and design of presentation interfaces with optimal usability/user experience
- Produces data models according to specific problems statements.
- Contribute to the design and implementation of the analytics architecture and its solution stack (including performance aspects, physical design, capacity dimensions etc…)
- Write the different documentation associated with the tasks and liaise with other project teams as necessary to address cross-project interdependencies.
- Interact with data stewards and other IT stakeholders to define the data rules;
- Define data controls and implement actions to ensure data quality and integrity;
- Creating automated anomaly detection systems and constant tracking of its performance;
- Data mining using state-of-the-art methods;
- Processing, cleansing, and verifying the integrity of data used for analysis; Participate in the design of the IT architecture for solutions in the NLP / ML / AI fields
- Analyse data architecture for consistency, completeness, accuracy and reasonableness;
- Contributing for the analysis of data management vision, strategy and policy and derive the IT requirements;
- Analysis of Business requirements.
- Documentation of Business requirements.
- Business model analysis.
- Business process analysis.
- Business processes modelling
- Functional requirements and business cases analysis.
- Risk analysis.
- Assistance in Business cases, Vision documents, Project Charters and Security Plans.
LEVEL OF EDUCATION: Bachelor or Master Degree
KNOWLEDGE AND SKILLS:
- Good knowledge of natural language processing systems lifecycle and agile software development methodologies.
- Experience in the field of corpus-based linguistics.
- Experience with alignment models and classification methods.
- Experience with data analytics over big datasets, non-structured databases as well as data lakes.
- Good knowledge of information systems matters.
- Good knowledge of large organisation administrative business processes.
- Good knowledge of analysis/modelling tools and techniques (use case diagram, state diagram, entity relationship model, interaction diagrams etc.).
- Good knowledge of BPMN or UML or other with equivalent value.
- Good knowledge of Wiki and collaborative sites.
- Knowledge of software development methodologies (e.g., RUP, Agile).
- Excellent knowledge of Data Analytics techniques and tools.
- Experience in Machine Learning and Natural Language Processing.
- Experience with languages like R, Python, PERL.
- Good knowledge of business intelligence tools (Tableau, Qlik, SAS, SAP, GoodData…)
- Expertise in the ETL processes and tools (SAS, Talend Open Studio…)
- Good knowledge of SQL tooling (NoSQL DB, MongoDB, Hadoop, SQL)
- Knowledge of architectural design and implementation of scalable modern data stores.
SPECIFIC EXPERTISE:
- Excellent knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, and/or artificial intelligence frameworks.
- Knowledge of Large Language Models.
- Knowledge in one of the following areas: predictive (forecasting, recommendation), prescriptive (simulation), sentiment analysis, topic detection, social media crawling and processing, plagiarism detection, trends/anomalies detection in datasets, recommendation systems
- Knowledge of Graph Databases.
Levels: 10
Delivery mode : Near Site (Brussels)
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