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Quantitative Researcher (Fixed Income)
Posted by Old Mission on 24 March 2025, 564 days ago. Still on their Greenhouse board when we checked 39 min ago.
Read out of the posting
LevelNot stated
Experience askedNot stated
EmploymentNot stated
LocationChicago, IL, United States
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2025-03-24
Found viagreenhouse, direct from their system
We saw it 19 months after it went up.
The posting, as the company wrote it
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.
About the Position
Old Mission Capital, a global quantitative proprietary trading firm, is currently hiring a talented Quantitative Researcher to join our growing Fixed Income operation. The ideal candidate will have experience trading fixed income assets, corporate bonds, and other debt instruments. This Quantitative Researcher will be familiar with building and improving the firm’s risk and pricing models, as well as understanding the risks in trading these assets.
Responsibilities
Perform exploratory data analysis on various market datasets, including bond data, exchange quote data, and third-party pricing data, generate trading signals and evaluate how they might be applied.
Research and develop quantitative models to forecast bonds and commodities’ various metrics, including price, bid-ask spread, liquidity, etc, prototype predictive models, and perform regressions and other machine learning analysis to validate, backtest, and improve quantitative models.
Contribute to the development and continuous assessment of trade execution.
Required Skills
Qualified candidates will have an advanced degree in a quantitative field (preferably a Ph.D. in engineering, statistics, mathematics or a hard science).
Candidates need to have exceptionally high mathematical and programming skills (must be proficient in Python, VBA, or R).
Strong quantitative, analytical, research-oriented and problem-solving skills.
Superior communication, both written and verbal, and has the ability to handle multiple tasks in a time-sensitive, fast-paced, collaborative, collegial environment.
Successful candidates will have a passion for the financial markets and will have an entrepreneurial mindset as the team is growing and this individual will be a value-added contributor who will have an immediate impact.
Demonstrated experience in US corporate bonds is required.
Qualified candidates will have previous experience in TCA, execution quality assessment, and execution algorithms with a focus on US Credit.
Must have experience with credit pricing, credit curve models, and RFQ-based trading is desirable.
Must have experience with Bayesian filtering/Hidden Markov Models is desirable.
Intra-day credit curve modeling is a plus.
Benefits and Perks
Fully paid Medical, Dental, Vision, Disability, and LIfe Insurance
Fully stocked kitchen; free breakfast and lunch every day on-site
Tuition Reimbursement Program
401(k) with employer match
Paid Vacation, Sick, and Parental leaves
Commuter and Flexible Spending Program
Base Salary Range
$175,000 - $250,000 - Salaries are based on numerous factors such as skills, experience, and education. Our compensation package also includes a discretionary bonus
and a comprehensive benefits program for full-time employees. For more information, reach out to your recruiter.
Old Mission is not accepting unsolicited resumes from any staffing/search firms. All resumes submitted by staffing/search firms to any employee at Old Mission via-email, the Internet or directly without a valid signed search agreement will be deemed the sole property of Old Mission, and no fee will be paid in the event the candidate is hired by Old Mission.
Copied from Old Mission’s own board, not rewritten. Original ↗
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