Data Science Specialist Group Legal

Are you ready to work on data science projects to drive digital transformation? Join our newly established Data and Analytics Team within Group Legal and play a key role in redefining data as an asset. Collaborate closely with IT teams, data analysts, and architects to design and deliver cutting-edge AI solutions that enhance business capabilities.
We are seeking a senior data scientist to: Work with various stakeholders to translate reporting requirements into actionable tasks and implement product enhancements. Design, build, and deploy high-performance AI/ML/NLP models to meet business objectives. Monitor and optimize model performance, ensuring quality, stability, and scalability. Clean, manipulate and process raw data into useful information to be suitable for business purposes. Validate AI/ML opportunities, define business cases, and create roadmaps for implementation. Document model performance, governance, and validation processes comprehensively. Mentor and guide junior data scientists and analysts, fostering technical excellence across the team. You ll be part of the Data and Analytics Team within Group Legal s COO function a culturally diverse and collaborative group with members in multiple locations. The team s mission is to manage Group Legal s data as a strategic asset, ensure compliance with the Bank-wide Data Management Framework (DMF), and deliver advanced analytics and reporting solutions. You ll develop expertise in the technical tools and services that power our capabilities. A minimum of 3 years of experience delivering data science projects, either in a leading consultancy or in-house at a large organization. Proficiency in developing end-to-end ML and NLP solutions, including data sourcing, feature engineering, model training, evaluation, and visualization. Experience in state-of-the-art ML algorithms (e.g., XGBoost, Neural Networks) and techniques (e.g., supervised, unsupervised, or reinforcement learning). Proficiency in building ML & NLP / LLM solutions using common ML libraries and frameworks (e.g. Pandas, Sklearn, TensorFlow, Transformers, OpenAI, Huggingface) Hands-on experience with NLP applications such as named entity recognition, text classification, sentiment analysis, or chatbot development. Familiarity with MLOps practices, containerized solutions (Docker, Kubernetes), and cloud platforms like Azure, AWS, or Google Cloud. Ability to explain technical concepts to non-technical stakeholders. A strong team player and communicator.