Description

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

You will own the development and implementation of predictive analytics to support investment strategies, leveraging time series analysis on financial markets data. You will build and maintain data infrastructure, ML pipelines, and dashboards to track performance while collaborating with front-office teams to identify data-driven opportunities.

Responsibilities

• Design and deploy statistical models and machine learning algorithms for investment strategies.
• Utilize time series analysis on fixed income assets and financial market data.
• Develop and maintain data pipelines, ML infrastructure, and CI/CD processes for app deployment.
• Create data dashboards and reports to monitor investment performance.
• Collaborate with cross-functional teams to integrate data solutions into asset management workflows.

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.

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