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USA · Hybrid

Quantitative Research Scientist

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

1. 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.

2. 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.

3. 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.

4. 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.


Locations
USA
Remote status
Hybrid
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USA · Hybrid

Quantitative Research Scientist

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