Description

Apply advanced statistical modeling and machine learning to financial market data, focusing on Fixed Income assets and investment banking.

Responsibilities

• Design and deploy statistical models and time series analysis for financial markets.
• Collaborate with data engineers to source, analyze, and engineer features for large-scale datasets.
• Develop, test, and deploy machine learning models within production environments.
• Build and manage ML and data pipelines to support application deployment via CI/CD.
• Present complex technical findings to technical peers and non-technical leadership.

Required Skills

• 14+ years of experience in data science, with at least 6 years in Financial, Investment, Asset Management, or Fixed Income sectors.
• Advanced proficiency in Python and/or R.
• Deep expertise in Machine Learning (Supervised, Unsupervised, Recommendation engines, Optimization) and Deep Learning (RNN, CNN, LSTM, Autoencoders, GANs).
• Hands-on experience with PySpark, Keras, and TensorFlow.
• Strong knowledge of Natural Language Processing and Generative AI/Language Models.
• Proficiency in SQL and at least one NoSQL database.
• Experience working with cloud platforms such as AWS, Azure, or IBM.
• Experience with CI/CD and ML pipeline deployment.
• Strong mathematical foundation in Machine Learning and statistical modeling.

Preferred Skills

• Experience in Asset Allocation, Research, or Quantitative Engineering.
• Background working in front-office roles within asset management firms.

Key Skills

Education

Bachelor's degree