Our client is a leading Investment Management firm and is looking to hire a Data Analyst to join their Quantitative Research and Investing (QRI) group within the Common Risk Platform (CRP) team. The team is responsible for data and tools that enable advisors across the organisation to measure and report on risk in their portfolios. This highly skilled team is responsible for a cross-asset, production platform for risk computation as well as the quality of input data to these computations and the correctness of the results.
In your role as Data Analyst you will be part of a team responsible for ensuring the accuracy of inputs to the risk platform and the quality of its outputs. Your work will involve building automated data quality checks and conducting ad hoc analyses to understand the accuracy of risk data. Your team is spread across the globe, with key colleagues in London with whom you can learn and grow. Your efforts will span deep technical aspects of datasets as well as high-level executive communication and interaction with quant researchers.
The successful candidate will have the following skills and experience:
- Data analysis and data quality work in the risk field, involving datasets including MSCI and Barra, with substantial fluency in risk reporting and metrics.
- Highly analytical with the ability to quickly comprehend large data sets in order to develop new processes, perform calculations, and identify anomalies.
- Ability to write complex queries in SQL across large datasets and to debug stored procedures.
- Expertise manipulating data in Python or R, including joining data, using statistics packages to categorise data and identify outliers, and automating data processes.
- Background in statistics, linear algebra and Calculus as applied to portfolio risk and anomaly detection.
- Domain expertise in financial datasets from vendors like Bloomberg and MSCI and tools such as BarraOne and RiskManager.
- Understanding of risk models and the computations behind them, with intuition for whether a risk value is sensible for a given portfolio or security.
- Detailed knowledge of multiple asset classes, including equities, fixed income, commodities and alternative investments, and the relevant analytics for each (e.g. financial ratios, duration, OAS, Greeks, implied vol.)
- Experience with data quality rules and frameworks for financial datasets.
- Experience with Cloud-native platforms (AWS, Snowflake, etc.)
- Experience working in agile environments using tools such as Jira, Confluence and GitHub.
- Highly proactive and self-motivated, able to meet objectives under minimal supervision.
- Degree, or higher, in computer science, engineering, mathematics, or finance.
Salary: £70K-90K + Bonus & Benefits