ETF Quant Researcher: Pricing & Trading Ideas

Ashby; Chicago (IL); On-site; USD 170,000 - 300,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Disability Insurance

Life Insurance

Free meals on-site

Tuition Reimbursement

401(k) with company match

Paid time off (vacation/sick/parental)

Job summary

Old Mission, a global trading firm, seeks a Quantitative Researcher for its Chicago ETF trading team. You will review and develop pricing models, analyze trades, and contribute ideas to improve models and algorithms.

The role partners with international and domestic teams to advance research and execution. You will work with large data sets, implement Python-based analytics, and collaborate in a fast-paced, entrepreneurial environment.

Qualifications

• Advanced degree in a quantitative field (CS, engineering, math, stats or hard sciences).
• 5+ years of experience in quantitative research preferred.
• Proficiency in Python required; VBA, R, Matlab, Java are plus.
• Strong written and verbal communication in a fast-paced, collaborative setting.
• Ability to work in a high-pressure team environment with multiple tasks.

Responsibilities

• Investigate pricing models for equities, commodities, and FX and propose improvements.
• Calibrate new models for various market environments.
• Reverse engineer how global markets behave in different conditions.
• Develop databases to support new ideas and research.
• Analyze market data and microstructure to explore trading ideas.
• Collaborate with traders and developers in idea-generation.

Education

Advanced degree in a quantitative field

Tools

Python

VBA

R

Matlab

Java

Job description

Old Mission, a global trading firm, seeks a Quantitative Researcher for its Chicago ETF trading team. You will review and develop pricing models, analyze trades, and contribute ideas to improve models and algorithms.

The role partners with international and domestic teams to advance research and execution. You will work with large data sets, implement Python-based analytics, and collaborate in a fast-paced, entrepreneurial environment.