Research, prototype, and back test options overlay strategies in Python with realistic assumptions for transaction costs, liquidity, and taxes across SMA accounts
Job Summary
Research, prototype, and back test options overlay strategies in Python with realistic assumptions for transaction costs, liquidity, and taxes across SMA accounts.
Monitor portfolio-level Greeks, exposures, and risk/return outcomes across many smaller accounts within rules-based risk parameters.
Partner with product managers and engineers to convert manual workflows and research into scalable platform capabilities — strategy engines, trade generation, risk dashboards, monitoring tools.
Matching Summary
Research, prototype, and back test options overlay strategies in Python with realistic assumptions for transaction costs, liquidity, and taxes across SMA accounts.