At C&IB Global Markets, our Advanced Analytics & Algorithmic Trading team is at the forefront of transforming our business into a more scientific and data-driven enterprise. We are seeking a highly skilled Algo Trading Quant to join our efforts in building a cutting-edge suite of trading algorithms for our Credit Flow Desks in New York.

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Key Responsibilities

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As part of our team, you will have the opportunity to work on impactful initiatives that blend quantitative finance with advanced technology, including:

• Development of Advanced Analytics Models: Design and implement models to estimate fair value, market liquidity, optimal bid-ask spreads, hedging strategies, and other pricing insights for credit instruments.
  
• Algorithmic Trading Solutions: Build and refine market-making and execution algorithms using scientific methodologies such as stochastic optimal control, machine learning, and reinforcement learning.
  
• Signal Generation: Develop predictive indicators and alpha signals based on market trends, volatility, volume, inflation metrics, and other relevant features.
  
• Performance Analysis: Create robust frameworks for ex-ante (backtesting) and ex-post (P&L attribution) evaluation of models and algorithmic strategies.
  
• Trader Collaboration: Work closely with credit trading desks in London and New York to understand their business goals, translate those into quantitative models, and iteratively refine your solutions based on trader feedback.
  

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Ideal Candidate Profile

We are looking for a candidate with strong quantitative acumen and a passion for applying data science to financial markets. You should possess:

• Education: A Master's degree in Physics, Mathematics, Statistics, Engineering, or Computer Science.
  
• Experience: 3–5 years in a quantitative research, algorithmic trading, or data science role within the financial industry or a similarly rigorous environment.
  
• Market Knowledge: Solid understanding of financial markets. Familiarity in credit trading instruments and strategies is a plus
  
• Mathematical Fluency: Ability to conceptualize and communicate complex ideas in mathematical terms. Proficiency in stochastic calculus, Bayesian methods, and optimal control theory is a strong plus.
  
• Programming Skills:
  
  • Proficient in Python and object-oriented languages such as Java.
    
  • Knowledge of KDB+/Q is highly valuable.
    
• Data & ML Tools: Experience with common machine learning libraries and big data technologies such as Hadoop and Spark.
  
• Soft Skills:
  
  • Entrepreneurial mindset with the initiative to identify and pursue opportunities.
    
  • Ability to work under pressure and deliver results in fast-paced environments.
    
  • Strong communication skills in English; Spanish is a plus but not required.
    

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