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Quantitative Analyst; Fully Remote
Remote / Online - Candidates ideally in
UAE/Dubai
Listed on 2026-02-28
UAE/Dubai
Listing for:
RGG Capital
Full Time, Part Time, Remote/Work from Home
position Listed on 2026-02-28
Job specializations:
-
Finance & Banking
Data Scientist
Job Description & How to Apply Below
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 Analys
t 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 Responsibiliti es:Hedge Fu
- nds:
Conduct comprehensive quantitative analysis of hedge fund returns, risk metrics, and factor exposures to evaluate manager skill and strategy persist - ence Develop and maintain proprietary analytical frameworks to decompose hedge fund performance, identify style drift, and assess risk-adjusted returns across market cy
- cles Perform detailed attribution analysis to validate managers' stated investment processes and verify alignment with reported res
- ults Build and maintain risk factor models to evaluate strategy correlations, beta exposures, and potential portfolio overlaps across our manager univ
- erse Analyze portfolio-level characteristics including liquidity profiles, position-level concentration, and counter party expos
- ures Provide quantitative support to the CIO for manager evaluation and ongoing monito
- ring Create detailed analytical reports for the investment committee, synthesizing complex quantitative findings into actionable insi
- sses:
Acquire, clean, and normalize various alternative datasets (e.g., sentiment, social media, and ESG sou - rces)
Develop and refine predictive models and signals using time-series analysis, statistical modeling, and machine learning - erning
Create robust backtesting frameworks to evaluate model performance and incorporate transaction cost or market i - mpact
Build and monitor risk models, conduct stress testing under different market scen - arios
Document and present research findings, methodologies, and performance metrics to stakeho
- ations
Master's degree in Finance, Economics, Mathematics, Computer Science, Engineering, Financial Engineering, Statistics, or a related quantitative field (re - quired)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 tradin
- g firm)
Proven track record of building and validating quantitative models in real-world market enviro - nments.
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 fram - eworks.
Familiarity with statistical techniques (time-series analysis, regression, factor modeling, signal proce - ssing).Solid understanding of financial market structure, pricing, and liq
- uidity.
Knowledge of key asset classes (equities, fixed income, or deriva - tives).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 e
- ications
PhD in a quantitative field (Financial Engineering, Statistics, or - similar).Experience analyzing sentiment or alternative data (news feeds, social media, ES
- G, etc.).Background in machine learning, deep learning, or NLP for financial for
- ecasting.
Familiarity with cloud computing environments (AWS, GCP, or Azure) for large-scale data pr - ocessing.
Experience with portfolio optimization, risk analytics, or factor i
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