Job Description:

The Senior Data Analyst will be a key contributor to the analytical functions in support of the business's strategic decision-making process. With a strong foundation in SQL and Python, the ideal candidate will possess in-depth knowledge and experience in the capital markets or banking domain. This role involves working with large datasets, extracting insights, and providing actionable recommendations to drive business growth and efficiency.

Responsibilities:

• Develop and maintain complex SQL queries for data analysis and extraction.
• Use Python for data manipulation, cleaning, and analysis, leveraging libraries such as Pandas, NumPy, and SciPy.
• Manage and ensure the integrity of large datasets essential for analysis.
• Translate data into meaningful insights that address business questions and opportunities.
• Create and automate reports, dashboards, and visualizations using tools like Tableau, Power BI, or similar.
• Present complex analytical findings in a clear, concise manner to stakeholders and executive teams.
• Work closely with business units to identify and analyze core business processes and workflows.
• Facilitate data-driven decision-making by providing timely, accurate, and relevant information.
• Collaborate with cross-functional teams including IT, Finance, Risk Management, and Operations to support company objectives.
• Communicate complex data concepts and the implications of analyses to a non-technical audience.
• Support strategic initiatives through scenario modeling and impact analysis.
• Contribute to the development and implementation of new data analysis methodologies.
• Maintain an up-to-date understanding of the capital markets or banking industry trends, regulations, and best practices.
• Apply domain knowledge to enhance data analysis and interpretation.

Requirements:

• Minimum of 7 years of experience in a data analysis role within the capital markets or banking sector.
• Expertise in SQL and Python is a must.
• Strong analytical and problem-solving skills.
• Experience with data visualization and business intelligence tools (e.g., Tableau, Power BI).
• Excellent verbal and written communication skills.
• Ability to work independently and manage multiple tasks and projects.
• Understanding of data warehousing and ETL processes.

Knowledge of statistical modeling and machine learning techniques is a plus