Senior Quantitative Researcher — Market Microstructure — Austin

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

Benefits offered by this job

Medical insurance

Dental & vision

401(k) plan

Paid time off

Parental leave

Learning budget

Home-office support

Bonus & equity eligibility

Job summary

Anemoi Predictive Technology LLC in Austin, TX is seeking a Senior Quantitative Researcher focused on market microstructure. The role studies intraday price formation, liquidity, and execution behavior across U.S.

equities and requires base in the Austin area for Central Time collaboration with research, engineering, and trading teams. The position offers a fully remote arrangement with a base salary of $210,000–$285,000 USD plus a performance bonus and equity eligibility depending on role and

Qualifications

• Advanced degree in a quantitative field or an 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 review during Central Time collaboration.

Skills

Python

SQL

Statistics

Market data experience

Empirical research

Education

Advanced degree or equivalent research record

Job description

This fully remote Senior Quantitative Researcher — Market Microstructure opening serves Austin, TX and will research intraday price formation, liquidity, and execution behavior across U.S. equities. Applicants must be based in the Austin, TX area. The position adds Central Time collaboration between quantitative research, engineering, and trading operations.

Compensation and Benefits

Base salary: $210,000–$285,000 USD, based on experience
Work arrangement: Fully remote; applicants must be based in the Austin, TX area
Experience: 7+ years
Additional compensation: Performance-bonus and equity eligibility based on role and level

About the Role

The Austin, TX position owns the full evidence path from event-time data design through production review of market-microstructure measures. Its working schedule covers Central Time collaboration between quantitative research, engineering, and trading operations. You will work with a small group of specialists and preserve enough evidence for another person to challenge every material decision.

Austin Operating Focus

The Austin opening emphasizes reproducible experiments, production discipline, and direct technical communication. This opening sits at the boundary between research ideas and production systems. Experiments must be reproducible, data lineage must remain visible, and a promising result does not bypass release controls. Central Time overlap supports direct work with both coasts, while written design records keep asynchronous review effective. For this role, that means direct ownership of event-time data quality, liquidity diagnostics, and intraday research review during Central Time collaboration between quantitative research, engineering, and trading operations.

First Review Cycle

Your first documented cycle for the Austin, TX opening will test the operating process for event-time data quality, liquidity diagnostics, and intraday research review during Central Time collaboration between quantitative research, engineering, and trading operations. The objective is a reproducible baseline, not a quick narrative. Your initial work includes this task: Design studies of spreads, depth, impact, auction behavior, and short-horizon price response. It also includes this task: Build event-time datasets without look-ahead or survivorship bias. The Austin opening emphasizes reproducible experiments, production discipline, and direct technical communication. The review must preserve the timing and source of each important input. At the end of the cycle, you will show how the evidence supports or challenges the full evidence path from event-time data design through production review of market-microstructure measures. Open questions stay visible until another review resolves them.

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 Central Time collaboration between quantitative research, engineering, and trading operations.

Required Qualifications

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

Preferred Qualifications

• Experience with order-book data, auctions, or transaction-cost models
• A record of explaining noisy microstructure evidence without overstating conclusions
• Experience collaborating across time zones while maintaining the operating coverage assigned to the Austin, TX opening.

Benefits

• Medical, dental, and vision plan options with substantial company support
• 401(k) plan with company matching
• Flexible paid time off and company holidays
• Paid parental and caregiver leave
• Annual learning, conference, and professional-development budgetRemote-work equipment and home-office support
• Performance-bonus and equity eligibility based on role and level

Benefits are subject to plan terms and eligibility requirements.

Equal Opportunity

Anemoi provides equal employment opportunities without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or any other status protected by applicable law.