Data & Quant Analyst

We are seeking a highly skilled Quantitative Data Analyst to provide business insights and support for Trading, Execution, and Sales teams. This role focuses on developing quantitative models, building data pipelines, and creating dashboards to drive data-driven decision-making across trading floor.

Key Responsibilities:

• Conduct statistical analyses to generate actionable insights for Trading, Execution, and Sales teams.
• Design and implement quantitative models for Market Making, Order Execution, and Delta One desks.
• Develop and maintain data pipelines and dashboards tailored to various trading floor use cases.
• Ensure data accuracy by mining, cleaning, and analyzing large datasets for effective use-case development.
• Write clean, well-documented code in Python to optimize and automate trading workflows.
• Support the Markets Data Analytics team in business development efforts, working with external vendors, managing schedules, preparing reports, and creating presentations.
• Build and maintain software applications, user interfaces, APIs, and automated reports to support business functions.
• Present findings related to business performance and Data Science methodologies to stakeholders.
• Contribute to the development of the Data Analytics platform, including database and Data Lake architecture.
• Collaborate with Data Scientists, Developers, and Traders to meet project timelines.

Key Requirements:

• Master’s or PhD in Statistics, Mathematics, Physics, Engineering, Economics, or a similar field.
• At least 4 years of experience as a Quantitative Analyst or Data Analyst in the finance sector.
• Proficiency in Python coding.
• Advanced skills in Power BI, Tableau, and VBA/Power Query.
• Strong background in Quantitative or Algorithmic Trading.
• Knowledge of Machine Learning methods, including clustering, factor modeling, reinforcement learning, and advanced statistical techniques.
• Understanding of Mathematical Finance and Financial Markets, such as Algorithmic Trading, Derivatives, Portfolio Management, and Numerical Methods.
• Familiarity with Agile methodologies, Scrum, and Jira.
• Experience with Git, SQL, Spark, and Dash or similar tools.
• Exposure to cloud platforms such as Microsoft Fabric, Azure Synapse, Databricks, and Snowflake.
• Additional experience with MLOps tools (e.g., Dataiku), R, or Scala is a plus.
• Strong communication skills, attention to detail, and the ability to present technical findings to non-technical audiences.