Lead Data Scientist — Full-Stack AI in Production

Salt; Abu Dhabi; On-site; AED 350,000 - 650,000; Full time

Job summary

Salt is building a new AI Lab and seeks a Lead Data Scientist to drive AI initiatives from concept to production. The role requires hands-on coding, model development and deployment across the full tech stack.

You will lead a team of data scientists, mentor peers, and shape the technical direction of AI solutions for banking use cases, leveraging modern ML frameworks and cloud platforms.

Qualifications

• 8+ years of experience in Data Science, ML, AI Engineering or related field.
• Degree in Computer Science, AI, ML, Mathematics, Statistics, Engineering or similar quantitative discipline.
• Hands-on Python development and strong SQL.
• Proven track record of taking ML/AI models into production.
• Solid understanding of software engineering principles: Git, APIs, testing, CI/CD, containerisation.
• Experience with cloud platforms such as AWS, Azure or GCP.
• Familiarity with PyTorch, TensorFlow, Hugging Face, LLMs, RAG, vector databases, and agentic AI.
• Banking/fintech exposure is advantageous.

Responsibilities

• Lead design, development and deployment of AI/ML solutions across banking use cases.
• Own full lifecycle from problem definition to deployment, monitoring and optimisation.
• Develop production-grade solutions using Python, SQL and modern ML/AI frameworks.
• Build and productionise GenAI, LLM, RAG, NLP and related AI solutions.
• Collaborate with Data Engineers, Software Engineers and Product teams to move AI into production.
• Develop robust ML pipelines, APIs, model-serving components and MLOps processes.
• Establish best practices for model deployment, testing, monitoring and reproducibility.

Skills

Python

SQL

Full-stack data science

CI/CD

Containerization

Education

Bachelor's or Master's in Computer Science / AI / ML / Math / Statistics

Tools

Git

APIs

Docker

Kubernetes

Job description

Salt is building a new AI Lab and seeks a Lead Data Scientist to drive AI initiatives from concept to production. The role requires hands-on coding, model development and deployment across the full tech stack.

You will lead a team of data scientists, mentor peers, and shape the technical direction of AI solutions for banking use cases, leveraging modern ML frameworks and cloud platforms.