Job description
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.
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 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.
• Excellent communication and interpersonal skills to collaborate with cross-functional teams, conduct training sessions, and promote data governance best practices.
SPECIFIC EXPERTISE:
• Excellent knowledge of machine learning techniques and algorithms, and 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.
• Knowledge of application UI/UX design.