• Manages and participate in the management of Data Management projects executed by the Data Management Section.
• Assists, supports and follows-up on strategic data related projects, products and initiatives executed by other agencies in client.
• Assists and follows-up on the implementation of strategic data related systems and applications, procedures, policies and guidelines.
• Ensures completeness, maintenance and accuracy of data governance within client and the Data Science and Analytics systems and environments including metadata, operating models and standards.
• Maintains current and future data architecture and environments of client’s Data Science and Artificial Intelligence lab including tuning, monitoring and altering data model, and managing user groups.
• Configures and updates the Data Science and Artificial Intelligence Lab components to ensure alignment with best practices and strategic vision.
• Manages the improvement of client Data Science and Artificial Intelligence Lab and Data Management Section functions.
• Creates and manages users’ access security and permissions to the environment within client’s Data Science and Artificial Intelligence lab.
• Manages the deployment of approved data products developed within the Data Science and Artificial Intelligence Lab onto target systems/applications.
Requirements
• Bachelor degree in Computer Engineering or Computer Science/IT or equivalent from recognized university.
• 6 years of relevant experience in a large and active service organization.
• Experience in Business Intelligence or Data Analysis.
• Working knowledge of PDW, Hadoop, SQL and RDBMS systems (DB2, Oracle, SQL Server, etc.)
• Strong knowledge in programming languages such as Scala and Python3, and Experience with common data science toolkits, such as R, Scikit-learn, MatLab, etc.
• Excellent understanding of Machine Learning techniques and algorithms, including supervised (Random Forest, XGBoost, Neural Networks, etc.) and non-supervised (K-Means, DBScan, etc.). with experience in deploying machine learning models in production using container-based technologies and orchestration systems like Kubernetes, as well as ML pipelines with Oozie and/or Airflow.
• Excellent understanding of data visualization tools based on Python (Bokeh, Matplotlib, Pyplot, etc.), R (GGPlot2), JavaScript (D3Js, HighChart, etc.).
• Experience in using query languages such as SQL, Hive, Pig, and with NoSQL databases, such as MongoDB, Cassandra, HBase, Neo4J, etc.