Old Mission
Finance
JuniorQuantitativeResearcher(Ph.D.)
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Junior Quantitative Researcher (Ph. D. ) at Old Mission. Skills: Quantitative research, Derivative pricing models, Volatility modeling, Python programming, C++ programming. Conceptualize and implement cutting-edge derivative pricing models for single-asset derivatives. Develop pricing models for widely traded equity volatility products such as variance swaps, volatility swaps, and VIX options”
Industry & Context.
Team-oriented problem solver
What They're Looking For.
Must Have
Masters or Ph. D. in a quantitative discipline (computer science, engineering, physics, mathematics, statistics, or other hard sciences), Programming skills in Python and C++
Nice to Have
Experience with dividend swaps and futures
What You'll Do.
Conceptualize and implement cutting-edge derivative pricing models for single-asset derivatives
Develop pricing models for widely traded equity volatility products such as variance swaps
Evaluate existing options pricing models
scrutinizing aspects such as calibration accuracy and Greeks stability
Investigate and propose enhancements to address identified issues in pricing models
Develop more resilient and stable alternative options pricing models
Explore and suggest new parameterizations for the volatility surface
Design improved filtering rules for market data quotes during calibration
Develop options specific research infrastructure and libraries in Python
Analyze market data and microstructure to identify patterns
Facilitate the exploration of trading ideas
Actively participate in the idea generation process for options research
Contribute insights and innovations to options research
Collaborate closely with traders
Engage in the analysis of data with traders
Jointly develop new tools and ideas with traders
Identify patterns in the market
How You'll Work.
Team & Collaboration
Collaborate directly with our options trading group; Collaborate closely with traders; Engage in the analysis of data and jointly developing new tools and ideas with traders
Communication Scope
Exceptional written and verbal communication skills
Process & Methodology
Manage multiple tasks in a time-sensitive, collaborative, and fast-paced environment, Managing multiple work streams concurrently
Full Job Description
Old Mission is a global proprietary trading firm that leverages state-of-the-art technology and research to identify and execute profitable trading strategies across multiple asset classes around the world. Our offices in Chicago, New York, and London are all composed of naturally-curious individuals who thrive in a team environment and constantly strive for improvement. Old Mission does not seek capital from outside investors, allowing us the flexibility to aggressively invest in our team members and keep them engaged in the firm’s growth. About the Position We are actively seeking a Quantitative Researcher (Ph.D.) to join our Chicago office. In this role, you will collaborate directly with our options trading group, contributing to the enhancement of existing pricing models, and spearheading the development of cutting-edge models and tools. The primary focus will be on efficiently pricing volatility-based derivatives across diverse asset classes. As a key member of the team, you will actively participate in the options research idea generation process and may also take the lead in expanding the capabilities of the quant team to further enhance the options desk. Responsibilities Conceptualize and implement cutting-edge derivative pricing models for single-asset derivatives, as well as pricing models for widely traded equity volatility products such as variance swaps, volatility swaps, and VIX options. Evaluate existing options pricing models, scrutinizing aspects such as calibration accuracy and Greeks stability to identify any anomalies. Investigate and propose enhancements to address identified issues. Develop more resilient and stable alternative options pricing models, including exploring and suggesting new parameterizations for the volatility surface and designing improved filtering rules for market data quotes during calibration. Develop options specific research infrastructure and libraries in Python. Analyze market data and microstructure to identify patter
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