Quantitative Researcher – Options & Volatility (PhD)

Ashby; Chicago (IL); On-site; USD 175,000 - 250,000; Full time

Benefits offered by this job

Medical, Dental, Vision, Disability, &

On-site meals and free breakfast/lunch

Tuition Reimbursement Program

401(k) with employer match

Paid vacation, sick, and parentalLeave

Commuter benefits

Job summary

Old Mission is a global proprietary trading firm with offices in Chicago, New York, and London. We seek a Quantitative Researcher (Ph.D.) for the Chicago office to enhance pricing models and lead development of new tools for pricing volatility-based derivatives across asset classes.

You will collaborate with the options trading group, calibrate models, improve filtering rules, and create robust research infrastructure in Python. Strong quantitative background and Python/C++ skills are essential.

Qualifications

• Masters or PhD in a quantitative discipline (e.g., CS/engineering/physics/math/statistics).
• Proficient in derivatives and volatility modeling; pricing forward curves and volatility surfaces; knowledge of variance derivatives, VIX, etc.
• Proficiency in Python and C++ is required.

Responsibilities

• Conceptualize and implement pricing models for single-asset derivatives and volatility products.
• Evaluate calibration, Greeks stability, and improve pricing models and data handling.
• Develop research infrastructure and libraries in Python for options research.

Skills

Quantitative degree

Python

C++

Derivative pricing

Communication

Team player

Attention to detail

Ethics

Education

Masters or PhD in a quantitative discipline

Job description

Old Mission is a global proprietary trading firm with offices in Chicago, New York, and London. We seek a Quantitative Researcher (Ph.D.) for the Chicago office to enhance pricing models and lead development of new tools for pricing volatility-based derivatives across asset classes.

You will collaborate with the options trading group, calibrate models, improve filtering rules, and create robust research infrastructure in Python. Strong quantitative background and Python/C++ skills are essential.