Data Scientist

A world-leading banking group is looking for A Data Scientist with Hands-on development experience in ML and LLM

The ideal candidate should be:

• Multi-talented and can tech-lead, research and develop NLP technologies and frameworks custom tailored to the company needs.
• An influencer and be able to mentor and build his team members to grow professionally and personally.
• Able to collaborate with internal clients and stakeholders to facilitate access to data, infrastructure and finally, deployment.

What will you do?

• Work with the GenAI team lead to develop AI/GenAI projects.
• Research cutting edge technologies and trends in the GenAI field and suggest adoption strategies.
• Build strong working relationships with product managers leading multiple projects as you will be accountable for your team members’ deliverables and quality of output.
• Design, implement and enhance code libraries, and develop new algorithms and services for:

Text understanding using unsupervised and supervised approaches.

Combine text and layout processing to improve document parsing.

Develop natural language query facilities to drive intelligent data retrieval and analysis.

Explore text generation approaches for producing reports, summaries and responses.

Deliver production quality code libraries and components.

• Establish and maintain DS and NLP best-practices and methodologies to build and keep our technology leadership.

What should you bring?

• 3+ years’ experience as a data scientist or research engineer in a known software company.
• 3+ years of experience in Python (preferred) or other programming languages.
• Hands-on development experience in ML and LLM - MUST
• M.Sc. in Engineering, computer science or related field - MUST
• Proven experience in working using SCRUM.
• Experience working independently,
• Demonstrated critical thinking,
• Experience working with technical management teams to develop systems, solutions, and products.
• Analytical and problem-solving experience with large-scale systems.
• Experience working across multi-disciplinary teams and multiple partners in different time zones.