Data Analysis-Jobs in Vereinigte Arabische Emirate

The Department
Capital Markets IT (CMI) is the IT department within the bank focused on solutions related to Capital Markets. Capital Markets IT involves technology solutions and systems used in financial markets for trading, investment, and related activities. This includes electronic trading platforms, risk management systems, market risk, counterparty risk, algorithmic trading, data analytics, and regulatory measures. The use of advanced technologies like cloud and artificial intelligence is also becoming increasingly prevalent in capital markets to enhance efficiency and decision-making processes.

Job Responsibilities

1. Responsible for the design, development, maintenance of applications and systems as well as IT production and management of the Bank's technical infrastructures.
2. At the forefront of technological innovation, its teams provide technical and functional support for the development activities and projects of the various Corporate and Investment Banking professions in an international environment.
3. Develop and implement advanced machine learning and deep learning models to automate and transform business processes in the capital markets value chain.
4. Use and create data science models to produce strategic insights, develop sophisticated predictive models and deploy solutions meeting current standards.
5. Use generative AI models to create synthetic financial data, simulate market scenarios, generate new investment ideas, automate post-trade processes, and enrich seller interactions with relevant stakeholders.
6. Collaborate with quantitative analysts and traders to design solutions based on artificial intelligence.
7. Develop a product mindset on the exploitation of AI models to improve and build functional blocks in the IS ecosystem.
8. Work closely with technical and business teams to resolve complex problems.

1. Experience required 10 years minimum in an IT functional architecture position or equivalent role.
2. Expertise in machine learning, deep learning, generative AI and MLOps.
3. Knowledge of data management practices to clean, preprocess and transform data sets for model training.
4. Mastery of AI algorithms and frameworks (e.g., Tensorflow, PyTorch, Scikit, etc.).
5. Knowledge of GEN AI and LLM technologies on the public Cloud using RAG patterns.
6. Understanding the ethical principles to better generate embeddings for GenAI.
7. Expertise in Python, .NET or Java, DevOps / MLOps / LLMOps (GitLab CI/CD, Kubernetes, AWS Cloud).

1. Excellent problem-solving and analytical skills.
2. Effective communication skills and ability to work collaboratively in a team.
3. Excellent aptitude, curious to learn and inquisitive.
4. Autonomous, self-motivated and excellent team player.