Are you passionate about data science and eager to make a real impact in asset management? As an NLQ/LLM Data Scientist, you’ll help transform investment processes and client experiences with innovative natural language and machine learning solutions. You’ll collaborate with talented teams, continuously learn, and drive meaningful change using the latest data science techniques. Join us to advance your career and shape the future of investment management.

As an NLQ/LLM Data Scientist in the Asset Management Data & Analytics team, you will design and implement natural language interfaces that enhance decision-making and optimize operational processes. You will work closely with business stakeholders, technologists, and control partners to deploy solutions into production. Your expertise will generate actionable insights and improve client experiences, while you stay at the forefront of data science innovation.

 

Job Responsibilities:

Collaborate with internal stakeholders to identify business needs and develop NLQ solutions that drive transformationApply large language models, machine learning techniques, and statistical analysis to enhance decision-making and workflow efficiencyCollect and curate datasets for evaluation and continuous improvementPerform experiments with model architectures, hyperparameters, and evaluation metricsMonitor and improve model performance through feedback and active learningWork with technology teams to deploy and scale models in productionDeliver written, visual, and oral presentations of modeling results to stakeholdersStay current with research in LLM, ML, and data science, leveraging emerging techniques for ongoing enhancement

 

Required Qualifications, Capabilities, and Skills:

Degree in a quantitative or technical discipline, or practical industry experienceExperience in data science roles such as data engineering, ML engineering, LLM engineering, or data analyticsAdvanced Python programming skills with production-quality coding experienceExperience working with structured and unstructured dataExperience in prompt engineering and domain adaptationUnderstanding of foundational ML algorithms such as clustering and decision treesAbility to communicate complex concepts and results to technical and business audiences

 

Preferred Qualifications, Capabilities, and Skills:

Proficiency with SQL and SnowflakeExperience in Asset ManagementExperience applying NLP, LLM, and ML techniques to solve business problems such as semantic search, information extraction, question answering, summarization, personalization, classification, or forecasting