Quantitative Researcher — Systematic Equities — Colorado Springs

Anemoi Predictive Technology LLC.; Colorado Springs (CO); Hybrid; USD 175,000 - 245,000; Full time

Benefits offered by this job

Medical, dental, and vision plan

401(k) plan with company matching

Flexible paid time off and company abs

Paid parental and caregiver leave

Annual learning, conference, and pro‑f

Remote-work equipment and home-office

Performance-bonus and equity

Job summary

Anemoi Predictive Technology LLC. in Colorado Springs, CO, is seeking a Quantitative Researcher — Systematic Equities to develop and test systematic equity research across sectors, factors, and market regimes.

This fully remote position requires residency in the Colorado Springs area to align with Mountain Time coverage. The role demands 3+ years of quantitative research experience, Python and SQL proficiency, and a solid grasp of backtest bias and model validation.

Qualifications

• Three or more years in quantitative research, data science, or systematic investing.
• Proficiency in Python and SQL with strong probability and statistics.
• Clear understanding of backtest bias and model validation.

Responsibilities

• Form hypotheses and build clean point-in-time equity datasets.
• Test signal stability, turnover, capacity, and transaction-cost sensitivity.
• Run walk-forward and out-of-sample evaluation.
• Present both favorable and unfavorable results to the investment team.
• Own equity-signal validation, sector diagnostics, and regime review during Mountain Time coverage spanning early preparation, the cash session, and late review.

Skills

Quantitative research

Data science

Systematic investing

Probability and statistics

Backtest bias awareness

Model validation

Tools

Python

SQL

Job description

This Colorado Springs, CO-based, fully remote Quantitative Researcher — Systematic Equities position will develop and test systematic equity research across sectors, factors, and changing market regimes. Applicants must live in the local area, which gives the team Mountain Time coverage spanning early preparation, the cash session, and late review.

Compensation and Benefits

Base salary: $175,000–$245,000 USD, based on experience
Work arrangement: Fully remote; applicants must be based in the Colorado Springs, CO area
Experience: 3+ years
Additional compensation: Performance-bonus and equity eligibility based on role and level

About the Role

In this Colorado Springs, CO role, you will be accountable for a falsifiable research idea from point-in-time data construction through out-of-sample evaluation while supporting Mountain Time coverage spanning early preparation, the cash session, and late review. The work requires direct communication, explicit limits, and records that remain useful after market conditions change.

Colorado Springs Operating Focus

The Colorado Springs opening emphasizes resilient operations, precise handoffs, and calm response to market exceptions. Mountain Time coverage connects pre-market preparation with a full view of later-session behavior. The opening maintains resilient procedures for missing data, system degradation, and unusual liquidity. When an exception occurs, the response must be calm, reversible where possible, and detailed enough for independent review after conditions normalize. For this role, that means direct ownership of equity-signal validation, sector diagnostics, and regime review during Mountain Time coverage spanning early preparation, the cash session, and late review.

First Review Cycle

For the first complete work cycle in Colorado Springs, CO, you will use Mountain Time coverage spanning early preparation, the cash session, and late review to test how the team measures and escalates changes in equity-signal validation, sector diagnostics, and regime review. One required check is: Form hypotheses and build clean point-in-time equity datasets. The next required check is: Test signal stability, turnover, capacity, and transaction-cost sensitivity. The Colorado Springs opening emphasizes resilient operations, precise handoffs, and calm response to market exceptions. You will identify any assumption that remains untested after both checks. The closing record identifies the evidence, approval, limit, and next test. A second specialist must be able to evaluate a falsifiable research idea from point-in-time data construction through out-of-sample evaluation from the same starting facts.

Responsibilities

• Form hypotheses and build clean point-in-time equity datasets
• Test signal stability, turnover, capacity, and transaction-cost sensitivity
• Run walk-forward and out-of-sample evaluation
• Present both favorable and unfavorable results to the investment team
• Own equity-signal validation, sector diagnostics, and regime review during Mountain Time coverage spanning early preparation, the cash session, and late review.

Required Qualifications

• Three or more years in quantitative research, data science, or systematic investing
• Python and SQL proficiency with strong probability and statistics
• Clear understanding of backtest bias and model validation

Preferred Qualifications

• Experience with equity factors, corporate actions, and point-in-time fundamentals
• A record of moving research into monitored production use
• Experience collaborating across time zones while maintaining the operating coverage assigned to the Colorado Springs, CO 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 budget
• Remote-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.