Description Job Description As an innovative data scientist within the Data Science team, you will design and implement ML solutions to enhance investment processes, elevate client experiences, and streamline operations. Initially, you will be focused on developing solutions to support our ESG and Stewardship functions with a heavy focus on content extraction, search and principals-based reasoning with LLMs. Your technical expertise will drive impactful results, and you’ll play a key role in shaping our data science capabilities. You’ll thrive in a collaborative culture that values hands-on problem solving and continuous learning. Your technical expertise will drive impactful results, and you’ll play a key role in shaping our data science capabilities. You’ll thrive in a collaborative culture that values hands-on problem solving and continuous learning. Job Responsibilities Collaborate with internal stakeholders to understand business needs, build out requirements, and design technical architectures Develop technical solutions utilising LLMs with a focus on problems involving search, content extraction and principal-based reasoning Build comprehensive evaluation packages to ensure the efficacy and reliability of solutions and to build trust with stakeholders Collaborate heavily with engineering functions to deliver high quality, scalable output Stay up to date with the latest developments in AI and become an SME within the data science function Required qualifications, capabilities, and skills Master's degree or a PHD in Computer Science or Engineering or quantitative or STEM discipline. Experience delivering AI/ML product and managing stakeholder relationships Proven experience in NLP and working with LLMs Proficiency in programming languages such as Python and familiarity with ML libraries and frameworks Excellent communication skills and ability to work collaboratively in a fast-paced, dynamic environment Good understanding of the foundational principles and practical implementations of statistics and machine learning algorithms such as supervised and un-supervised learning, deep learning, reinforcement learning, etc. Preferred qualifications, capabilities, and skills Strong analytical skills with an understanding of financial markets and asset management line of business Business domain knowledge in ESG, investment stewardship, or buyside investment CFA or equivalent financial qualification