Vice President - Data Science - NLP/LLM/Modeling/Python - BFS

Must Have:

- This will be a part of the global team, hence the candidate needs to have global exposure

- IC role

- 4+ years is required for Advanced python programming skills

- Current experience in applying NLP, LLM and ML techniques and candidates with good modeling exp (model development)

- Banking / financial background is highly preferred

- Asset & Wealth Management background will be good to have but not mandate

- Good Education Pedigree

- EMEA Shift

- Mini 3 days WFO

Job Responsibilities

- Collaborate with internal stakeholders to identify business needs and develop NLP/ML solutions that address client needs and drive transformation.

- Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to enhance informed decision-making and improve workflow efficiency, which can be utilized across investment functions, client services, and operational process.

- Collect and curate datasets for model training and evaluation.

- Perform experiments using different model architectures and hyperparameters, determine appropriate objective functions and evaluation metrics, and run statistical analysis of results.

- Monitor and improve model performance through feedback and active learning.

- Collaborate with technology teams to deploy and scale the developed models in production.

- Deliver written, visual, and oral presentation of modeling results to business and technical stakeholders.

- Stay up-to-date with the latest research in LLM, ML and data science. Identify and leverage emerging techniques to drive ongoing enhancement.

Required qualifications, capabilities, and skills

- Advanced degree (MS or PhD) in a quantitative or technical discipline or significant practical experience in industry.

- Minimum of 8 years of experience in applying NLP, LLM and ML techniques in solving high-impact business problems, such as semantic search, information extraction, question answering, summarization, personalization, classification or forecasting.

- Advanced python programming skills with experience writing production quality code

- Good understanding of the foundational principles and practical implementations of ML algorithms such as clustering, decision trees, gradient descent etc.

- Hands-on experience with deep learning toolkits such as PyTorch, Transformers, HuggingFace.

- Strong knowledge of language models, prompt engineering, model finetuning, and domain adaptation.

- Familiarity with latest development in deep learning frameworks.

- Ability to communicate complex concepts and results to both technical and business audiences.

Preferred qualifications, capabilities, and skills

- Prior experience in an Asset Management line of business

- Exposure to distributed model training, and deployment

- Familiarity with techniques for model explainability and self validation