Multibank Group - Senior Data Scientist
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
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
Benefits
• 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.
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