DESCRIPTION OF THE TASKS:
1. Policy Support: Collaborate with policy officers to analyze large datasets to provide data-driven actionable recommendations and insights for decision-making.
2. Data Analysis and Modelling: Conduct exploratory data analysis, build predictive models, and extract insights from large datasets.
3. Algorithm Development: Develop and implement machine learning algorithms to optimize tax collection, risk assessment, and fraud detection, typically in a cloud environment.
4. Collaborate with data engineers to ensure data availability and quality.
5. Implement data-driven solutions to optimize business processes and outcomes.
6. Communicate findings and recommendations to stakeholders in a clear and concise manner.
7. Follow up and coordinate all efforts on design, implementation, and operations of data platform capabilities on analytical and algorithmic models of a cloud solution.
8. Ensure the necessary requirements are complied with from the perspective of data scientist users.
9. Design and deliver prototype versions of analytic models to utilize AI, deep learning, or other techniques in the technical capabilities of a cloud solution.
10. Design or participate in the design of data processing algorithms for specific use cases.
11. Report on the status, risks, and mitigation actions in this respect.
12. Data Visualization: Create clear and informative visualizations to communicate complex data findings to stakeholders.
SPECIFIC EXPERTISE:
1. Excellent knowledge of data analysis techniques and tools.
2. Proficient in developing and deploying machine learning models.
3. Strong knowledge of cloud platforms such as AWS, Azure, OVH or Google Cloud.
4. Proficiency (at least 3 years’ experience) with programming languages like Python, R.
5. Statistics and Probability, at least 3 years’ experience in:
1. Excellent knowledge of statistical concepts like mean, median, mode, variance, and standard deviation.
2. Excellent knowledge of distributions and sampling techniques.
6. SQL and Database Management, at least 3 years’ experience:
1. Excellent knowledge of SQL (Structured Query Language).
2. Knowledge of data wrangling, cleaning, and database design.
7. A specific specialization may be defined for Machine Learning and AI:
1. At least 3 years’ experience in building and training ML models using frameworks like Pandas, Scikit-Learn, Keras, TensorFlow, NumPy.
2. Good knowledge of natural language processing (NLP) and feature engineering.
8. Big Data Technologies:
1. Good knowledge of distributed computing frameworks like Hadoop and Spark.
2. Good knowledge of cloud platforms for scalable data processing.
9. Knowledge of data visualization tools such as Tableau, Power BI, or matplotlib.
10. Understanding of data governance and data quality principles.
Certification and/or Standards:
1. Optional certifications:
1. AWS Certified Machine Learning – Specialty
2. Microsoft Certified: Azure Data Scientist Associate
3. Google Professional Data Engineer
4. Cloudera Certified Data Scientist (CCP: DS)
Specific Skills:
1. Capability to produce IT architecture documents related to data science projects.
2. Research and Innovation: Stay up to date with the latest advancements in data science and contribute to innovative solutions.
3. Analytical Mindset: Ability to translate complex data into actionable insights.
Level: Senior
Delivery Mode: Near Site (Brussels)
#J-18808-Ljbffr