Description

Apply advanced statistical techniques and data modeling to drive investment decision-making and business growth in the fixed income sector.

Responsibilities

• Lead development and implementation of advanced data modeling and predictive analytics to support investment strategies.
• Utilize statistical modeling and time series analysis on financial markets data, including Fixed Income assets.
• Develop and maintain data infrastructure and ML pipelines to support data-driven decision-making.
• Oversee creation of data dashboards and reports to track investment performance.
• Collaborate with cross-functional teams to identify opportunities for leveraging data within front-office asset management roles.

Required Skills

• 14+ years of experience in data science, including designing and deploying statistical models.
• 6+ years of hands-on experience in Financial, Investment, Asset Management, or Fixed Income sectors.
• Advanced proficiency in Python and/or R.
• Expertise in Machine Learning (Supervised, Unsupervised, Recommendation engines, Optimization) and Deep Learning (RNN, CNN, LSTM, Autoencoders, GANs).
• Strong experience with PySpark, Keras, and TensorFlow.
• Deep understanding of Natural Language Processing (NLP) and Language Models.
• Proficiency in SQL and at least one NoSQL database.
• Experience with cloud platforms such as AWS, Azure, or IBM.
• Familiarity with data pipeline creation, app deployment (CI/CD), and ML pipelines.

Preferred Skills

• Experience with Generative AI and Large Language Models.
• Background in Asset Allocation, Research, or Quantitative Engineering.

Key Skills

Education

Bachelor’s degree in computer science