Summary
MultiBank Group is hiring a Senior Data Scientist for its AI and Machine Learning team in Dubai. The role involves developing and deploying machine learning models, LLM and multimodal applications, and agentic AI systems, while owning the model lifecycle and production monitoring. Candidates should have 5 to 10 years of relevant hands-on experience, strong Python skills, and expertise in deep learning, LLM tooling, and production ML pipelines. A degree in computer science, applied mathematics, statistics, or a related field is requested, though equivalent industry experience may be considered.
The posting
As published on multibankgroup.com. Pulled from the employer's site and shown as they wrote it.
Welcome to MultiBank Group, a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.
Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.
Role Overview
We are seeking a Senior Data Scientist to join our AI and Machine Learning team. 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. The successful candidate 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.
Key Responsibilities
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
Prototype and assess LLM-based and multimodal systems for document understanding, knowledge extraction, information retrieval, and workflow automation, including fine-tuning foundation models, building RAG pipelines, and extending models for domain-specific applications
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
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
Contribute to solution architecture and collaborate closely with data engineers, software engineers, and domain experts to integrate AI-enabled products into existing systems
Establish robust monitoring frameworks to evaluate AI solution performance post-deployment. Proactively identify data quality issues, model drift, and performance degradation, and drive continuous improvement initiatives
Stay current with advances in AI research, mentor junior data scientists, contribute to internal knowledge sharing, and support the broader AI community of practice within the organization
Requirements
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
Strong foundation in applied mathematics, probability, and statistics underlying modern ML and DL methods
Advanced Python programming skills with a focus on clean, production-ready code
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
Experience in the fintech sector is a strong advantage
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
Technical Stack
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
Why Join Us?
Work with one of the world’s leading financial derivatives institutions.
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.
Be part of a business committed to innovation, excellence, and long-term growth.
Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.
MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.