Data Analyst

Role Overview You will work closely with a variety of stakeholders, including Data Strategists and Data Engineers, as well as teams across Technology, Operations, Research, and Risk Management. The role involves investigating complex data issues, analyzing datasets, maintaining data quality, and supporting research teams in a fast-paced environment. What You Will Do

• Analyze new datasets to profile their content, identify collection and storage requirements, and proactively surface insights for Data Strategists and Front-Office stakeholders.
• Collect metrics and analyze datasets across key dimensions of data quality, including completeness, validity, accuracy, timeliness, and consistency.
• Curate and maintain data catalog entries to ensure research data assets are accurately represented and easily discoverable.
• Collaborate with global Front-Office Research teams throughout the data lifecycle, addressing data-related queries and managing communications with external data vendors.
• Monitor, investigate, and resolve production data issues while coordinating with key stakeholders across multiple teams.
• Identify opportunities to improve existing datasets, data quality processes, and overall data management practices.
• Document findings and communicate complex data analysis results clearly to both technical and non-technical stakeholders. What You Will Need
• 1–2 years of relevant experience in data analysis, data quality, data management, or a related field.
• Strong foundational knowledge of financial instruments and market data symbology, with an interest in developing further expertise.
• Proficiency in SQL and Python for exploratory data analysis, including Pandas, PySpark, and Jupyter Notebooks.
• Ability to investigate complex data issues and clearly document and communicate findings.
• Exceptional attention to detail, analytical thinking, and problem-solving skills.
• Strong written and verbal communication skills.
• Ability to work effectively both independently and collaboratively in a fast-paced environment. Skills : The following skills will be considered an advantage:
• Experience with cloud services such as AWS Athena and Amazon S3.
• Familiarity with Linux and basic Bash scripting.
• Experience with version control tools such as Git.
• Good understanding of data management and data quality principles, including experience developing data quality checks or reports.
• Prior experience using the Bloomberg Terminal.
• Experience with Apache Airflow or similar workflow orchestration tools.
• Familiarity with financial market data and research workflows. Key Skills
• SQL | Python | Pandas | PySpark | Data Quality | Data Analysis | Data Management | AWS Athena | Amazon S3 | Git | Linux | Bash | Apache Airflow | Financial Market Data