Quantitative Researcher - Execution & Market Impact

Tower Research Capital; New York (NY); On-site; USD 120,000 - 200,000; Full time

Benefits offered by this job

Generous paid time off

Savings plans

Hybrid work opportunities

Free meals daily

Wellness reimbursement

Sports & fitness events

Volunteer opportunities

Social events

Learning opportunities

Job summary

Tower Research Capital in New York seeks a Quantitative Researcher to build models, analytics, and decision systems that improve execution quality across global trading teams. The role sits at the intersection of market impact research, transaction cost analysis, causal inference, experiment design, optimization, and execution strategy.

The researcher will work on understanding and improving how orders are routed, scheduled, evaluated, and optimized across brokers, algorithms, venues, markets,

Qualifications

• Masters or Bachelor's in a quantitative field; PhD preferred.
• 2-5 years of quantitative research experience.
• Strong knowledge of statistics and time-series analysis.
• Experience with large financial datasets.
• Strong Python skills; C++/Rust a plus.

Responsibilities

• Research market impact, execution cost, slippage across global markets.
• Build models to explain and predict execution outcomes.
• Design and analyze A/B experiments for execution improvements.
• Develop causal inference methods.
• Create optimization models for execution objectives.
• Collaborate with traders, PMs, developers, and engineers to productionize research.
• Build calculators, dashboards, and reports for traders.

Skills

Python

Data analysis

Experiment design

Machine learning

Communication

Education

Masters or Bachelor's in a quantitative field

PhD preferred

Tools

C++

Rust

SQL

Job description

Tower Research Capital in New York seeks a Quantitative Researcher to build models, analytics, and decision systems that improve execution quality across global trading teams. The role sits at the intersection of market impact research, transaction cost analysis, causal inference, experiment design, optimization, and execution strategy.

The researcher will work on understanding and improving how orders are routed, scheduled, evaluated, and optimized across brokers, algorithms, venues, markets,