Jobs via eFinancialCareers
Sr FI Quant Researcher - DTG Capital Markets
Jobs via eFinancialCareers, New York, New York, us, 10261
Sr FI Quant Researcher - DTG Capital Markets
NYC based multi‑strategy hedge fund managing multi‑billion capital across discretionary, fundamental, and systematic strategies. The firm operates in a non‑pod structure fostering ultra‑close collaboration and cross‑disciplinary idea exchange. The firm emphasizes research excellence, technological innovation, and rapid idea implementation, offering researchers the ability to influence portfolio‑level decisions across multiple strategies.
Role Overview We are seeking a highly skilled Quantitative Researcher to join a team focused on fixed income derivatives trading. The role offers exposure to a blend of fundamental and systematic strategies, allowing researchers to generate alpha through both deep market intuition and quantitative innovation. In this highly collaborative environment, you will work closely with traders, quants, and technologists to research, design, and implement trading strategies.
Key Responsibilities Conduct bottom‑up and quantitative research in fixed income markets. Develop predictive alpha models that support fundamental and systematic trading decisions. Analyze yield curves, swap spreads, and vol surfaces, identifying relative value, arbitrage, and directional opportunities. Collaborate with engineers to productionize models, signal generation, and risk integration. Partner to integrate signals into portfolio construction and risk‑managed trade execution. Support the continuous enhancement of data and research infrastructure, including traditional and alternative datasets.
Required Qualifications 5+ years of quantitative research, with emphasis on alpha generation in fixed income derivatives. Open to equity derivatives background. Proficiency in Python, with experience in numerical libraries and data pipelines. Expertise in derivatives pricing and risk concepts -- Greeks, convexity, term structure sensitivities. Experience with large‑scale datasets, including tick, market, and alternative data. Excellent collaboration and communication skills; ability to thrive in a flat, team‑oriented environment. Advanced degree (Ph.D. or M.S.) in a quantitative discipline (Mathematics, Physics, Financial Engineering, Computer Science). Familiarity with cloud computing, cluster backtesting, or distributed data frameworks. Strong intuition combined with rigorous quantitative and statistical capabilities. Collaborative mindset: thrives in a flat, cross‑strategy environment. Comfortable innovating across asset classes and engaging directly with PMs, engineers, and other quants.
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Role Overview We are seeking a highly skilled Quantitative Researcher to join a team focused on fixed income derivatives trading. The role offers exposure to a blend of fundamental and systematic strategies, allowing researchers to generate alpha through both deep market intuition and quantitative innovation. In this highly collaborative environment, you will work closely with traders, quants, and technologists to research, design, and implement trading strategies.
Key Responsibilities Conduct bottom‑up and quantitative research in fixed income markets. Develop predictive alpha models that support fundamental and systematic trading decisions. Analyze yield curves, swap spreads, and vol surfaces, identifying relative value, arbitrage, and directional opportunities. Collaborate with engineers to productionize models, signal generation, and risk integration. Partner to integrate signals into portfolio construction and risk‑managed trade execution. Support the continuous enhancement of data and research infrastructure, including traditional and alternative datasets.
Required Qualifications 5+ years of quantitative research, with emphasis on alpha generation in fixed income derivatives. Open to equity derivatives background. Proficiency in Python, with experience in numerical libraries and data pipelines. Expertise in derivatives pricing and risk concepts -- Greeks, convexity, term structure sensitivities. Experience with large‑scale datasets, including tick, market, and alternative data. Excellent collaboration and communication skills; ability to thrive in a flat, team‑oriented environment. Advanced degree (Ph.D. or M.S.) in a quantitative discipline (Mathematics, Physics, Financial Engineering, Computer Science). Familiarity with cloud computing, cluster backtesting, or distributed data frameworks. Strong intuition combined with rigorous quantitative and statistical capabilities. Collaborative mindset: thrives in a flat, cross‑strategy environment. Comfortable innovating across asset classes and engaging directly with PMs, engineers, and other quants.
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