Remote Quantitative Researcher – United States – Drive Impact with Cutting-Edge Data Models

Join a fast‑growing fintech innovator where your quantitative expertise will shape next‑generation trading strategies and risk models. This fully remote role offers the flexibility to work from anywhere in the U.S. while collaborating with a global team of data scientists and engineers. If you thrive on turning complex data into actionable insights, this is the opportunity you’ve been waiting for.

About the Role

As a Quantitative Researcher, you will design, implement, and validate statistical models that power algorithmic trading, portfolio optimization, and risk management solutions. You will work closely with engineers to move research prototypes into production, ensuring models are robust, scalable, and compliant with regulatory standards. The position encourages continuous learning, offering access to cutting‑edge datasets, high‑performance computing resources, and mentorship from senior quant leaders.

Key Responsibilities

• Develop predictive models using machine learning, time‑series analysis, and stochastic calculus.
• Conduct rigorous back‑testing and stress‑testing to evaluate model performance under various market conditions.
• Collaborate with software engineers to translate research findings into production‑ready code (Python, C++, or Julia).
• Monitor model drift and implement recalibration strategies to maintain predictive accuracy.
• Present findings and recommendations to stakeholders through clear visualizations and technical reports.
• Stay abreast of academic literature and industry best practices, integrating novel techniques into the research pipeline.

Requirements

Education & Experience

• Master’s or Ph.D. in Mathematics, Statistics, Physics, Computer Science, Engineering, or a related quantitative field.
• 2+ years of experience in quantitative research, financial modeling, or data science (internships and academic projects count).
• Strong proficiency in Python or R; familiarity with C++/Java is a plus.
• Solid grasp of statistical inference, optimization techniques, and machine learning algorithms.
• Experience with financial time‑series, risk metrics, or trading strategies is highly desirable.

Technical Skills

• Expertise with libraries such as NumPy, pandas, scikit‑learn, TensorFlow/PyTorch, and MATLAB.
• Comfortable working with SQL and NoSQL databases for large‑scale data extraction.
• Knowledge of version control (Git) and containerization (Docker/Kubernetes) for reproducible research.
• Ability to write clean, efficient, and well‑documented code following software engineering best practices.

Benefits

• Competitive salary range: $110,000 – $150,000 USD/year (based on experience and qualifications).
• Full remote work flexibility – work from any location within the United States.
• Generous equity package aligned with company performance.
• Comprehensive health, dental, and vision insurance.
• 401(k) plan with company matching.
• Annual learning budget for conferences, courses, and certifications.
• Wellness stipend and mental‑health resources.
• Unlimited PTO plus company‑observed holidays.
• Access to state‑of‑the‑art cloud computing credits for research experiments.

Why Join Us?

We are a mission‑driven team passionate about leveraging quantitative rigor to create transparent, efficient financial markets. Our culture values curiosity, intellectual honesty, and collaborative problem‑solving. By joining us, you will have the autonomy to pursue ambitious research projects, the support of a world‑class engineering team, and the satisfaction of seeing your models directly influence real‑world trading decisions.