- Design, develop, train, and deploy machine learning models, including those for Computer Vision and Large Language Models (LLM), ensuring their robustness and scalability.

- Perform in-depth statistical analysis and create compelling data visualizations to communicate findings and recommendations effectively to stakeholders.

- Work extensively with SQL for data extraction and manipulation, ensuring data integrity and accessibility.

- Utilize Azure and implement MLOps practices to streamline the machine learning lifecycle, from experimentation to production deployment.

- Apply your understanding of Trade Life Cycle, Settlements, Inventory Management, or broader Investment Banking processes to solve real-world business challenges.

- Strategic Support : Provide data-driven recommendations to support strategic decision-making and optimize business operations.

What We're Looking For :

- 5 to 10 years of hands-on experience as a Data Scientist or ML Engineer.

- Strong expertise in Python for data science and machine learning.

- Proven experience with various Machine Learning Algorithms, Model Training, and Deployment.

- Hands-on experience with Computer Vision and/or Large Language Models (LLM).

- Proficient in Statistical Analysis, Data Visualization, and SQL.

- Practical experience with Cloud Platforms (Azure) and implementing MLOps practices.

- Solid understanding of Trade Life Cycle, Settlements, Inventory Management, or Investment

Banking operations.

- Excellent analytical, problem-solving, and critical-thinking skills.

- Strong ability to communicate complex technical concepts to non-technical stakeholders.