VP Applied AI - Deep Learning

ABOUT GOLDMAN SACHS:

Qualifications

• Required
• Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, Physics, Electrical Engineering, or a related quantitative discipline.
• Minimum of five years of professional experience in machine learning, quantitative research, applied research, data science, or a closely related field.
• Deep learning and representation learning
• Time-series forecasting and sequential modeling
• Quantitative finance, or market microstructure
• Demonstrated ability to formulate and independently execute rigorous research using large, complex, and high-dimensional datasets.
• Ability to communicate complex research ideas, empirical findings, and methodological trade-offs clearly and effectively.
• Ability to work independently on open-ended research questions while collaborating effectively with traders and engineers
• Experience with Transformer-based models, probabilistic deep learning, or other modern sequence architectures.
• Experience with multivariate forecasting, cross-sectional prediction, or high-frequency market data.
• Research experience in quantitative trading, systematic investing, market microstructure, electronic execution, market making, statistical arbitrage, or financial econometrics.
• Publications or demonstrated research contributions in leading machine-learning, artificial intelligence, statistics, optimization, or quantitative-finance venues.
• Demonstrated ability to connect methodological advances in AI with robust and economically meaningful results in financial markets.
• Advance frontier research in financial AI: Work on challenging research problems at the intersection of deep learning, Transformer-based modeling, time-series foundation models, and quantitative finance, with the opportunity to generate meaningful commercial impact.
• Access differentiated data and research resources: Apply modern AI methods to proprietary, high-quality cross-asset market data, supported by the computational resources needed for large-scale model training and empirical research.
• Join a rigorous research culture: Be part of a dedicated Applied AI research team that values scientific rigor, strong baselines, robust out-of-sample evaluation, reproducibility, and economically meaningful results.
• Collaborate on real market problems: Partner closely with quantitative researchers, strategists, and trading stakeholders across businesses to formulate impactful research questions in forecasting, alpha generation, liquidity, market microstructure, and execution.
• Engage with the broader research community: Contribute to thought leadership through internal research forums and, subject to applicable firm policies and approvals, external publications and engagement with the AI and quantitative research community.
• Shape the Applied AI research agenda: Develop deep expertise at the intersection of foundation models and financial markets, while helping define the team’s research priorities and future direction
• Salary Range

Preferred Qualifications

• Preferred
• The expected base salary for this New York, New York, United States-based position is $115,000-$30,0000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end.