Location: Washington, DC, Florida, or Texas Employment Type: Contract (3 months) Industry: Investment Management Role Overview We are seeking a highly analytical and mathematically driven Quantitative Research Scientist to join a leading investment management firm. The role focuses on developing a Market Risk Indicator (MRI) framework to support quantitative investment research and systematic investment strategies.
Key Responsibilities
- Quantitative Research & Model Development
- Research, understand, and implement the Log Periodic Power Law (LPPL) framework.
- Develop mathematical models to identify market bubbles, regime shifts, and potential market turning points.
- Extend the methodology to analyse multiple asset classes, including equities, bonds, commodities, currencies, cryptocurrencies, and macroeconomic indicators.
- Research and evaluate alternative market risk methodologies, including Turbulence Index models and other quantitative risk indicators.
- AI & Machine Learning
- Apply Artificial Intelligence and Machine Learning techniques to automate LPPL parameter estimation.
- Improve model calibration, optimisation, and prediction accuracy using modern data science methodologies.
- Explore innovative approaches for identifying financial anomalies and super-exponential growth patterns.
- Programming & System Development
- Develop clean, scalable, and reusable analytical code primarily in Python.
- Build flexible tools capable of analysing individual assets or multiple assets across custom and predefined time windows.
- Ensure outputs can be integrated seamlessly into the firm's internal dashboards and research infrastructure.
- Maintain documentation for models, assumptions, methodologies, and code.
- Financial Data Analysis & Research
- Analyse large financial and economic time-series datasets.
- Interpret model outputs and communicate research findings to investment professionals.
- Support continuous improvement of quantitative research methodologies and contribute to future research initiatives.
Education Qualifications
Master's or PhD in one of the following disciplines:
- Mathematics
- Data Science
- Computer Science
Ideal Candidate Profile
- 1–2 years of research or industry experience in quantitative modelling, data science, machine learning, or financial analytics.
- Strong mathematical, statistical, and analytical problem-solving skills.
- Experience in time-series analysis, optimisation, numerical methods, and statistical modelling.
- Proficiency in Python and scientific computing libraries such as NumPy, Pandas, SciPy, and scikit-learn.
- Working knowledge of Machine Learning and Artificial Intelligence techniques.
- Ability to independently understand and implement complex mathematical research with minimal supervision.
- Excellent programming skills with experience developing modular and maintainable code.
Compensation
USD 6k-8k per month.