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This is a high-paying opportunity for an experienced Data Analyst – Systematic Trading.
Job Title: Data Analyst – Systematic Trading
We are seeking a Data Analyst to join a systematic trading team within the volatility division of one of the world’s largest hedge funds. This role offers the opportunity to work in a front-office data analytics team, directly supporting multiple Portfolio Management (PM) teams to enable data-driven trading and investment decisions.
The firm operates a highly sophisticated data infrastructure, with a strong focus on data analytics and data science to drive systematic trading strategies.
Key Responsibilities:
- Source and onboard targeted data sets to enhance trading models and strategies.
- Build data pipelines and optimize ETL processes to ensure efficient data flow.
- Wrangle, analyze, and structure large datasets to support signal generation.
- Work closely with quantitative researchers, traders, and portfolio managers to translate data insights into trading opportunities.
- Maintain and optimize SQL databases and integrate with market data sources (e.g., Bloomberg).
Ideal Candidate:
- Strong Python and SQL expertise with hands-on experience in data analytics and pipeline development.
- Background in systematic trading, hedge funds, or financial markets.
- Understanding of multiple asset classes and their market data structures.
- Experience working with ETL processes and handling large datasets.
- Knowledge of Bloomberg or similar financial data platforms is a plus.
- Strong problem-solving skills with an ability to work in a fast-paced, high-pressure environment.
Compensation & Benefits:
- Highly competitive market-leading salary + performance-based bonuses.
- Hybrid work model – flexible working environment.
- Work within a cutting-edge, data-driven trading team at a globally recognized hedge fund.
- Opportunity for career growth in a highly technical and fast-moving environment.
Have a candidate who meets these qualifications? Don’t miss this opportunity! Submit their CV today!