MAIN TASKS
* Collect business requirements and analyse advanced AI solutions or identify and assess relevant existing data mining, machine learning and business intelligence solutions.
* Develop detailed application mock-ups using design tools, ensuring alignment with business objectives and user needs.
* Analyse large datasets to uncover actionable insights.
* Ensure strict compliance with GDPR and emerging AI regulations in all stages of data processing.
* Facilitate effective communication and collaboration between business stakeholders, data scientists, and IT developers.
* Conduct user acceptance testing to meet business requirements.
* Specification and design of presentation interfaces with optimal usability/user experience.
* Produce 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.
* Create 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.
* Participates in the design of the IT architecture for solutions in the NLP / ML / AI fields and coordinates its implementation considering master- and meta-data management concepts.
* 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.
EXPERTISE
* Good knowledge of natural language processing systems lifecycle and agile software development methodologies.
* 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 SQL tooling (NoSQL DB, MongoDB, Hadoop, SQL)
* Knowledge of architectural design and implementation of scalable modern data stores.
* Rapid self-starting capability.
* Strong capacity in preparing and writing business analysis.
* Capability to speak to business and technical audiences.
* Strong capacity to give high-level presentations.
* Excellent critical thinker, by using logic and reasoning to identify strengths and weaknesses of alternative solutions.