Senior Data Scientist

Role Overview

Senior Data Scientist at MultiBank Group, a global financial institution headquartered in Dubai, UAE. The role sits at the intersection of machine learning, computer vision, and large language models, with a focus on delivering production-grade intelligent solutions within a fintech environment.

Company Overview

MultiBank Group is a global financial pioneer established in 2005 in California and now headquartered in Dubai, UAE. The company specializes in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Product offerings include Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs. The institution serves over 2 million clients across 100 countries with daily trading volume exceeding US$ 35 billion. MultiBank Group is heavily regulated with oversight from 18+ financial regulators across 5 continents and has received over 80 financial awards.

Role Purpose

The Senior Data Scientist will contribute to AI strategy, lead end-to-end model development, and work closely with cross-functional teams across data engineering, software engineering, and business functions to deliver AI-enabled intelligent solutions in the fintech environment.

Key Responsibilities

Algorithm Development

• Design, develop, and evaluate data-driven algorithms across classification, detection, segmentation, regression, and anomaly detection, applying both classical and deep learning approaches.
• Rapidly prototype solutions and evaluate their performance against business objectives.

Large Language Models and Multimodal Systems

• Prototype and assess LLM-based and multimodal systems for document understanding, knowledge extraction, information retrieval, and workflow automation.
• Fine-tune foundation models and build RAG pipelines.
• Extend models for domain-specific applications.

Agentic AI Systems

• Design and implement agentic AI systems including task-oriented agents, workflow orchestrators, tool-using agents, and autonomous reasoning frameworks.
• Translate complex business workflows into reliable, observable, and maintainable AI-driven pipelines.

Machine Learning Lifecycle

• Own the full machine learning lifecycle from data collection, preparation, and cleaning through model training, evaluation, deployment, and ongoing production maintenance.
• Champion best practices in MLOps, versioning, and reproducibility.

Solution Architecture and Integration

• Contribute to solution architecture and collaborate closely with data engineers, software engineers, and domain experts to integrate AI-enabled products into existing systems.

Monitoring and Continuous Improvement

• Establish robust monitoring frameworks to evaluate AI solution performance post-deployment.
• Proactively identify data quality issues, model drift, and performance degradation.
• Drive continuous improvement initiatives.

Knowledge Leadership

• Stay current with advances in AI research.
• Mentor junior data scientists and contribute to internal knowledge sharing.
• Support the broader AI community of practice within the organization.

Qualifications & Experience

• 5 to 10 years of hands-on experience in classification, detection, and segmentation using both classical and deep learning approaches, applied to real-world, production-grade problems.
• Proven track record of developing, deploying, and scaling end-to-end ML pipelines in industrial or enterprise contexts.
• Hands-on experience building and deploying LLM applications including models such as GPT, Llama, Falcon, and Claude, covering fine-tuning, RAG systems, domain adaptation, and multimodal extensions.
• Experience designing and implementing agentic AI systems including task-oriented agents, workflow orchestrators, or autonomous reasoning frameworks.
• Experience collaborating in cross-functional teams and communicating technical outcomes to non-technical stakeholders.
• Bachelor's, Master's, or PhD in Computer Science, Applied Mathematics, Statistics, or a related field; strong candidates with equivalent industry experience will be considered.
• Experience in the fintech sector is a strong advantage.

Skills & Competencies

• Advanced Python programming skills with a focus on clean, production-ready code.
• Strong foundation in applied mathematics, probability, and statistics underlying modern ML and DL methods.
• Deep knowledge of ML algorithms and DL architectures including CNNs, Transformers, Diffusion models, and Graph Neural Networks.
• Proficiency in prompt engineering, evaluation frameworks, and structured output design for LLM-based systems.
• ML Frameworks: PyTorch, TensorFlow, Scikit-learn, XGBoost.
• LLM and Agentic Tooling: LangChain, LlamaIndex, Hugging Face, OpenAI and Anthropic APIs, LangGraph, AutoGen, CrewAI.
• MLOps and Development: ClearML, MLflow, Git, Docker, CI/CD pipelines, PyCharm, Jupyter.

Additional Information

• Competitive salary plus performance-based incentives.
• Access to a dynamic, international, and fast-growing environment.
• Strong opportunities for career progression within a global financial group.
• MultiBank Group is an equal opportunity employer and welcomes applications from candidates of all backgrounds without discrimination based on nationality, gender, age, religion, or disability.