Senior Quant Researcher — Market Microstructure (Remote)

Anemoi Predictive Technology LLC; Columbus, Northern (OH, KY); Hybrid; USD 210,000 - 285,000; Full time

Benefits offered by this job

Medical, dental, and vision

401(k) matching

PTO and holidays

Parental and caregiver leave

Learning budget

Remote equipment and home-office

Bonus & equity eligibility

Job summary

Anemoi Predictive Technology LLC in Columbus, OH is seeking a Senior Quantitative Researcher focused on Market Microstructure. The role researches intraday price formation, liquidity, and execution behavior across U.S.

equities, with Eastern Time monitoring and a balanced schedule for research and live-market review. Responsibilities include designing studies of spreads, depth, and price impact; building event-time datasets free of look-ahead bias; and collaborating with engineering to

Qualifications

• Advanced degree in a quantitative field or equivalent research record.
• Strong Python, SQL, statistics, and market-data experience.
• Evidence of rigorous empirical research in electronic markets.

Responsibilities

• Design studies of spreads, depth, impact, auction behavior, and short-horizon price response
• Build event-time datasets without look-ahead or survivorship bias
• Partner with engineering to productionize validated measures
• Document assumptions, failure modes, and regime sensitivity
• Own event-time data quality, liquidity diagnostics, and intraday research review during Eastern Time monitoring with a balanced schedule for research and live-market review

Skills

Python

SQL

Statistics

Market data

Education

Advanced quantitative degree

Job description

Anemoi Predictive Technology LLC in Columbus, OH is seeking a Senior Quantitative Researcher focused on Market Microstructure. The role researches intraday price formation, liquidity, and execution behavior across U.S.

equities, with Eastern Time monitoring and a balanced schedule for research and live-market review. Responsibilities include designing studies of spreads, depth, and price impact; building event-time datasets free of look-ahead bias; and collaborating with engineering to