VP, Applied AI & Deep Learning — Financial Time-Series

Goldman Sachs (lateral); New York (NY); On-site; USD 250,000 - 450,000; Full time

Job summary

Goldman Sachs is seeking a Senior Applied AI Research Engineer (Vice President level) in New York, to push the boundaries of deep learning and quantitative finance. You will lead end-to-end research projects, from framing questions to deploying insights for trading desks and engineers.

The role emphasizes responsible AI, reproducible research, and collaboration with cross-functional teams to turn complex data into actionable strategies.

Qualifications

• Ph.D. in a quantitative field relevant to ML and finance.
• Five+ years of professional ML/data science/quantitative research experience.
• Strong research background in ML or quantitative disciplines.

Responsibilities

• Conduct original research at the frontier of deep learning, time-series modeling, and quantitative finance.
• Develop novel predictive and representation-learning methods and evaluate their relevance.
• Own research end to end: data curation, model design, large-scale training, and evaluation.

Skills

ML/Quantitative research experience

Deep learning

Time-series modeling

Education

Ph.D. in Computer Science, ML, Statistics, Math, Physics, EE, or related quantitative discipline

Job description

Goldman Sachs is seeking a Senior Applied AI Research Engineer (Vice President level) in New York, to push the boundaries of deep learning and quantitative finance. You will lead end-to-end research projects, from framing questions to deploying insights for trading desks and engineers.

The role emphasizes responsible AI, reproducible research, and collaboration with cross-functional teams to turn complex data into actionable strategies.