Eu - Data Scientist - Brussels - European Goverments
il y a 3 semaines
**DESCRIPTION OF THE TASKS**:
Following tasks will be performed by external service provider:
- Collect business requirement and develop advanced data mining solutions or identify, assess and deploy relevant existing data mining, machine learning and business intelligence solutions.
- Specification and design of presentation interfaces with optimal usability/user experience.
- Identify, collect, convert and update different data types/sets in several locations (e.g. ETL).
- Produces data models according to specific problems statements.
- Scripting and programming.
- 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.
**LEVEL OF EDUCATION**:
As stated in the Article 2.6.3.1. of DIGIT-TM II Service requirements, a minimum educational qualification for lot 2 is: Level of education corresponding to Level 6 of the European Qualification Framework which typically corresponds to a bachelor degree of 3 years.
**KNOWLEDGE AND SKILLS**:
The following skills and knowledge are required for the performance of the above listed tasks:
- Very good knowledge of the involved Mathematics and Statistics (Linear algebra, Calculus, Probability theory, Statistics, hypothesis testing, Optimization techniques, etc.).
- Very good knowledge of programming in Python and/or R.
- Very good experience with data manipulation: Analysis techniques, ability to clean, pre-process, and transform data.
- Very good experience with data visualization using tools like Matplotlib, etc.
- Very good knowledge of ETL (Extract, Transform, Load) processes and techniques.
- Hands-on experience with various machine learning algorithms, including supervised, unsupervised, and reinforcement learning.
- Experience with model evaluation, selection and validation techniques.
- Knowledge of deep learning and neural networks.
- Experience with RDBMS like Oracle (latest version).
- Understanding of NoSQL databases like MongoDB or Cassandra.
- Knowledge of NLP techniques and libraries like NLTK, spaCy, or Transformers.
- Awareness of involved ethical considerations in data collection and analysis.
- Knowledge of applicable data privacy laws and regulations.
- Ability to give business and technical presentations.
- Ability to cope with fast changing technologies used in the domain of Data Science.
- Good communication skills with technical and non-technical audiences.
- Ability to convey complex findings to both technical and non-technical stakeholders.
- Storytelling with data: Presenting insights in a compelling and understandable way.
- Analysis and problem-solving skills.
- Capability to write clear and structured documents/reports.
- Capability of integration in an international/multicultural environment, rapid self-starting capability and experience in working in team;
- Ability to participate in multilingual meetings;
- Ability to work in multi-cultural environment, on multiple large projects;
- Excellent Team Player
- Ability to understand, speak and write French (B1/B2) will be an advantage;
**SPECIFIC EXPERTISE**:
N.A.
**CERTIFICATIONS & STANDARDS**:
N.A 4
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