KEY REQUIREMENTS:

• Bachelor Degree in Statistics, Mathematics, Engineering, Economics, or a similar field.
• At least 5 years of experience as a Data Analyst/Market Data Analyst in the finance sector.
• Good understanding of financial markets, trading instruments and market data feeds (Stocks, options, forex, futures)
• Proficiency in Python, R or Julia
• Strong understanding of data modelling, data warehousing and ETL processes
• Advanced skills in Power BI, Tableau, SQL, Excel and VBA/Power Query.
• Experience working with large data sets using SQL/Azure Data Lake/Spark/Databricks to derive actionable insights is preferred
• Knowledge of Machine Learning methods, including clustering, factor modeling, reinforcement learning, and advanced statistical techniques is an advantage
• Understanding of Mathematical Finance and Financial Markets, such as Algorithmic Trading, Derivatives, Portfolio Management, and Numerical Methods.
• Familiarity with Agile methodologies, Scrum, and Jira.
• 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.

• 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.