Verition Fund Management LLC (“Verition”) is a multi-strategy, multi-manager hedge fund founded in 2008.  Verition focuses on global investment strategies including Global Credit, Global Convertible, Volatility & Capital Structure Arbitrage, Event-Driven Investing, Equity Long/Short & Capital Markets Trading, and Global Quantitative Trading.

We are seeking a highly motivated AI/ML Quantitative Analyst with a PhD to join a world class firm that is in the process of implementing AI in number of different areas. The successful candidate will leverage advanced AI and machine learning techniques to support both trading strategies as well as other business functions across a diverse investment management platform. This role offers a unique opportunity to work at the intersection of finance and technology, collaborating with both quantitative researchers and fundamental traders.  This role is ideal for a recent PhD graduate who is passionate about applying AI and machine learning techniques to solve complex problems in the financial industry.

Responsibilities:

• Develop and implement AI and machine learning models to analyze financial data, generate predictive insights that support trading strategies and transform the firm’s business processes
• Perform in-depth data analysis, utilizing large datasets to identify trends, patterns, and anomalies that can inform investment decisions.
• Conduct research to develop and refine models, leveraging the latest advancements in AI/ML methodologies.
• Design and test models and algorithms to support trading strategies, ensuring they are robust, efficient, and scalable.
• Work closely with Portfolio Managers, Researchers, the Risk team and other business functions to integrate AI/ML models into the firm’s trading systems, strategies and business processes.
• Document research findings, model development processes, and performance metrics. Communicate results to both technical and non-technical stakeholders.

Qualifications:

• PhD ideally in AI/ML, but could be in STEM with a focus in AI/ML
• Prior experience in finance is a plus
• Proficiency in programming languages commonly used in AI/ML and quantitative finance, such as Python
• Strong knowledge of AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and experience applying AI/ML techniques to real-world data.
• Excellent quantitative skills with the ability to develop and interpret complex models and algorithms.
• Experience with data manipulation, cleansing, and preprocessing techniques. 
• Strong analytical and problem-solving skills, with a creative approach to developing innovative solutions.
• Ability to clearly communicate complex technical concepts to a diverse audience, including both technical and non-technical stakeholders.