Overview
This is a contractual role for a Financial Research Engineer working remotely from any location. The position involves researching and developing advanced financial models using computational techniques and AI-driven methodologies. The work supports the creation of predictive tools and automated financial systems that aid strategic business decisions.
Responsibilities
- Design, implement, and validate quantitative financial models using Python, statistical analysis, and machine learning algorithms.
- Research emerging trends in financial markets to identify patterns, anomalies, and predictive indicators for model enhancement.
- Collaborate with cross-functional teams to translate financial hypotheses into testable algorithms and validate their performance with real-world data.
- Optimize model efficiency and scalability to manage large-scale financial datasets while maintaining computational performance.
- Document research findings, methodologies, and model outputs for internal use and regulatory compliance.
Requirements
- Master’s degree or higher in Finance, Economics, Computer Science, or a related quantitative field.
- Minimum of 5 years experience in financial modeling, quantitative research, or algorithmic development within finance or fintech.
- Proficiency in Python, including libraries such as NumPy, Pandas, SciPy, and scikit-learn for financial data analysis.
- Strong expertise in statistical modeling, time-series analysis, and machine learning techniques applied to financial data.
- Experience handling large-scale financial datasets, including market data APIs, historical price feeds, or alternative data sources.
Compensation & Benefits
- Competitive payout based on experience.
Location
- Fully remote, work from anywhere.