Job Post!

Set and own the quantitative research agenda to build next generation valuation frameworks and systematic trading approaches spanning U.S. rates, swaps, and broader fixed income markets (10%). Scale systematic strategies in U.S. Treasuries, USD interest rate swaps, and related derivatives to monetize cross market dislocations and evolving liquidity regimes (10%). Embed advanced machine learning and alternative datasets into the full model lifecycledata curation, feature engineering, training, and live monitoringto enhance price discovery, execution quality, and risk insight (10%). Design a unified risk analytics stack delivering adaptive pre trade and post trade controls, P&L attribution, stress/scenario engines, and portfolio/strategy level diagnostics (5%). Translate research into robust, scalable production systems by partnering with senior trading leadership, technology, and risk to define SLAs, KPIs, experimentation guardrails, and reliability metrics (10%). Recruit, mentor, and manage a high performing quantitative team, setting technical standards (code quality, testing, documentation) and fostering a culture of innovation and continuous learning (10%). Modernize quantitative platforms and data pipelines by advancing automation, distributed computing, cloud/hybrid architectures, CI/CD, containerization, and resilient data engineering practices (5%). Maintain authoritative expertise in market microstructure, regulatory shifts, and trading technology trends to anticipate impacts on model design, execution venues, and risk frameworks (15%). Deliver executive level performance reviews and strategic recommendations, aligning research priorities with business objectives, capital allocation, and market opportunities (15%). Continuously evaluate and pilot emerging methodologies (e.g. robust optimization, reinforcement learning, causal inference) and drive their responsible adoption into the research roadmap (10%). Partial telecommuting permitted; on-site at 245 Park Ave., New York, NY 10167 when not telecommuting. MINIMUM REQUIREMENTS: Masters Degree or U.S. equivalent in Operations Research, Statistics, Finance, Financial Engineering, or related field, plus 4 years of professional experience as a Quantitative Advisor, Quantitative Analyst or any occupation/position/job title involving quantitative, programming, and statistical models for financial markets. Must also have the following: 4 years of professional experience in programming using Python, C# and SQL, applied to quantitative finance and algorithmic trading environments; 4 years of professional experience using statistical models to price and analyze financial products, including Black-Scholes, Local Volatility and Hull-White models; 4 years of professional experience developing post-trade analysis systems on algorithmic trading strategies performances, involving SQL databases interactions, data pipeline including Python Luigi and trading reports using Streamlit; 4 years of professional experience performing development and quantitative modeling analysis in Python, C# and Excel; 4 years of professional experience performing complex quantitative analysis on financial markets using stochastic models, numerical methods and optimization techniques, including ARIMA, PDE models, PCA, Regressions and Advanced Machine Learning frameworks; 4 years of professional experience in alpha generation for Fixed Income algorithmic trading strategies; 4 years of professional experience analyzing the performance of quoting algorithm within electronic trading framework; 4 years of professional experience analyzing portfolio performance and client trading behaviors using advanced statistical methodologies; and 4 years of professional experience developing and maintaining a pricing library with code sharing framework.CONTACT: Please email resume to: us-humn-recruitment@sgcib.com. Must specify Ad Code ZPAR in the subject line.