Data Scientist, AVP

Responsibilities

• Design, develop, and deploy machine learning and statistical models to provide market insights and drive data-driven decision-making.
• Analyze market, sector, corporate, and economic data to develop investment theses and produce high-quality research.
• Perform exploratory data evaluation to identify patterns, trends, and insights to build predictive and prescriptive analytics solutions.
• Present research views and complex data insights to clients through direct interactions, virtual meetings, and written communications.
• Collaborate with stakeholders, including Markets and Client Strategy, to raise awareness of research and navigate financial risks.
• Lead collaborative assignments, mentor junior team members, and guide team members through structured technical projects.
• Evaluate model performance and continuously improve accuracy and scalability while ensuring compliance with regulatory standards.

Requirements

• Proficiency in coding with Python, PySpark, R, or SQL.
• Strong understanding of machine learning and mathematical statistical modeling.
• Considerable academic background in a quantitative or empirical field such as Mathematics, Statistics, Economics, Computer Science, Physics, or Chemistry.
• Experience performing complex analysis of data from multiple internal and external sources.

Preferred Qualifications

• Demonstrated ability to communicate key implications and intuitions from highly detailed models to non-technical audiences.
• Experience with Snowflake or Databricks.
• Background in causal inference.
• Understanding of fundamental or strategic approaches to financial research.

About the Company

Barclays is a leading international financial institution dedicated to providing excellence in service and stewardship. We foster a culture of respect and integrity, empowering our people to challenge the status quo and drive innovation. Our team is composed of curious, hardworking, and collaborative professionals committed to making a meaningful difference in the global financial markets.