Quantitative Analyst; Fully Remote

Position: Quantitative Analyst (Fully Remote) Compensation: USD $130,000 per annum + up to 15% Performance Bonus Total Annual Package: Up to USD $149,500 Location: Remote We are seeking a Quantitative Analyst to join our data-driven research team focused on leveraging alternative data and sentiment analysis for market insights. This role emphasizes in-depth quantitative research, model development, and rigorous backtesting of signals to drive actionable strategies. The ideal candidate will have a passion for financial markets and expertise in transforming raw data into clear, data-informed insights. This position is remote, with the option to work from our Dubai office (with 0% income tax), if preferred (relocation and visa sponsorship support available). Key Responsibilities Hedge Funds • Conduct comprehensive quantitative analysis of hedge fund returns, risk metrics, and factor exposures to evaluate manager skill and strategy persistence • Develop and maintain proprietary analytical frameworks to decompose hedge fund performance, identify style drift, and assess risk-adjusted returns across market cycles • Perform detailed attribution analysis to validate managers' stated investment processes and verify alignment with reported results • Build and maintain risk factor models to evaluate strategy correlations, beta exposures, and potential portfolio overlaps across our manager universe • Analyze portfolio-level characteristics including liquidity profiles, position-level concentration, and counter party exposures • Provide quantitative support to the CIO for manager evaluation and ongoing monitoring • Create detailed analytical reports for the investment committee, synthesizing complex quantitative findings into actionable insights Other Asset Classes • Acquire, clean, and normalize various alternative datasets (e.g., sentiment, social media, and ESG sources) • Develop and refine predictive models and signals using time-series analysis, statistical modeling, and machine learning • Create robust backtesting frameworks to evaluate model performance and incorporate transaction cost or market impact • Build and monitor risk models, conduct stress testing under different market scenarios • Document and present research findings, methodologies, and performance metrics to stakeholders Required Qualifications • Master's degree in Finance, Economics, Mathematics, Computer Science, Engineering, Financial Engineering, Statistics, or a related quantitative field (required) • 3+ years of experience in quantitative research, data science, or analytics within a leading financial institution (e.g., top-tier investment bank, asset manager, hedge fund, or proprietary trading firm) • Proven track record of building and validating quantitative models in real-world market environments. • Proficiency in Python for data analysis (pandas, numpy, scipy) and modeling (stats models, scikit-learn). • Experience with databases (SQL or No SQL) and large-scale data processing frameworks. • Familiarity with statistical techniques (time-series analysis, regression, factor modeling, signal processing). • Solid understanding of financial market structure, pricing, and liquidity. • Knowledge of key asset classes (equities, fixed income, or derivatives). • Candidates must have completed all academic programs; those currently enrolled in part-time or full-time degree programs (e.g., part-time Master's, MPhil, PhD coursework) are not eligible Preferred Qualifications • PhD in a quantitative field (Financial Engineering, Statistics, or similar). • Experience analyzing sentiment or alternative data (news feeds, social media, ESG, etc.). • Background in machine learning, deep learning, or NLP for financial forecasting. • Familiarity with cloud computing environments (AWS, GCP, or Azure) for large-scale data processing. • Experience with portfolio optimization, risk analytics, or factor investing. #J-18808-Ljbffr