Junior PhD Quant Researcher: Options & Volatility (Python/C++)

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

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Disability insurance

Life insurance

On-site meals

Tuition reimbursement

401(k) with employer match

Paid vacation

Paid sick leave

Parental leave

Commuter benefits

Flexible spending accounts

Job summary

Old Mission Capital in Chicago seeks a Junior Quantitative Researcher (Ph.D.) to join the options research team. You will help enhance pricing models and develop new tools for pricing volatility-based derivatives across asset classes.

Collaborate with traders and researchers to broaden the quant team's capabilities, focusing on robust models, data analysis, and scalable Python infrastructure in a fast-paced environment.

Qualifications

• Master's or PhD in a quantitative field with expected graduation Summer 2027.
• Proficient in Python and C++ for pricing models.
• Experience with derivatives and volatility modeling.
• Strong communication and teamwork in fast-paced environments.

Responsibilities

• Implement derivative pricing models for single-asset derivatives.
• Price equity volatility products and variance/volatility swaps.
• Calibrate models and improve Greeks stability.
• Develop Python-based research infrastructure.
• Collaborate with traders to explore ideas.
• Analyze market data and microstructure.

Skills

Python

C++

Derivatives pricing

Volatility modeling

Greeks analysis

Team collaboration

Education

Masters or PhD in quantitative field

Tools

NumPy

Pandas

C++ libraries

Job description

Old Mission Capital in Chicago seeks a Junior Quantitative Researcher (Ph.D.) to join the options research team. You will help enhance pricing models and develop new tools for pricing volatility-based derivatives across asset classes.

Collaborate with traders and researchers to broaden the quant team's capabilities, focusing on robust models, data analysis, and scalable Python infrastructure in a fast-paced environment.