Senior Data Scientist

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 fina