Data Scientists/ ML Engineer - (AI/ML Specialists)

The company is currently looking for Data Scientists/ ML Engineers for our Bahrain operations with the following skillsets and terms & conditions.

Location
Bahrain

Requirements

• Bachelor’s Degree in Computer Science / Engineering (Preferably BE Computer Science & Engineering)
• 7 – 10 years of experience in banking, financial institutions, or insurance within AI/ML solutions
• Proven hands-on delivery experience with Gen AI solutions such as chatbots and document analysis

Professional Training Required

• Machine Learning, Deep Learning, MLOps, AI in Financial Services

Professional Certifications Required

• Google Professional ML Engineer
• Microsoft AI Engineer Associate
• TensorFlow Developer Certificate
• AWS Certified Machine Learning

Must-Have

• Several years of ML experience with implemented use cases
• Ability to build and deploy ML models using Python and relevant libraries
• Understanding of supervised and unsupervised learning algorithms

Job Responsibility

• Design and develop machine learning models to support AI-driven banking solutions
• Collaborate with data engineers to access and prepare data for modeling
• Apply statistical and ML techniques to solve business problems (e.g., churn prediction, credit scoring)
• Evaluate model performance and optimize for accuracy, precision, and recall
• Deploy models into production using MLOps frameworks and CI/CD pipelines
• Ensure models are explainable, auditable, and compliant with regulatory standards
• Work with business stakeholders to identify AI opportunities and define success metrics
• Document model assumptions, data sources, and performance benchmarks

Core AI / NLP Engineering

• Proficiency in Python (PyTorch, TensorFlow, LangChain, etc.)
• Experience with Retrieval-Augmented Generation (RAG) and vector databases
• Knowledge of embeddings, tokenization, and transformer architecture

Software Engineering & Backend Integration

• Experience with RESTful and GraphQL APIs, webhooks
• Familiarity with containerization and deployment (Docker, Kubernetes, CI/CD)
• Integration with enterprise data systems

Joining time frame
15 - 30 days