Data Scientist - Systematic Centralized Team
Our client is seeking a Data Scientits to join their Data Services team, a group responsible for sourcing, onboarding, managing, and delivering critical datasets used by quantitative researchers and portfolio managers across global systematic investment strategies. This team sits at the center of the research process, partnering closely with investment teams to ensure high-quality data is available for alpha generation, portfolio construction, and risk management.
A few highlights:
- Partner directly with Portfolio Managers, Quantitative Researchers, and Data Scientists supporting live systematic trading strategies
- Evaluate, onboard, and maintain a wide range of datasets, including alternative data, market data, fundamental data, and reference/security master data
- Build and enhance scalable data pipelines and ETL frameworks using Python and SQL
- Develop data quality, validation, and monitoring processes to ensure research-ready datasets
- Create derived datasets, features, and analytics used in alpha research and model development
- Work on large-scale data infrastructure supporting billions of dollars in trading capital
- Gain exposure to the full lifecycle of quantitative research and systematic investing
- Highly visible role with direct interaction across technology, data, and investment teams
- Strong compensation package with significant bonus upside
Ideal Background:
- Experience working with market data, security master, reference data, alternative data, or research data platforms
- Strong Python and SQL skills
- Experience building data pipelines, ETL workflows, and data quality frameworks
- Familiarity with cloud technologies, distributed data processing, or modern data stack tools is a plus
- Exposure to quantitative research, asset management, hedge funds, systematic trading, or financial data environments is highly preferred
This is an excellent opportunity for someone who enjoys combining data engineering, analytics, and investment-facing work in a highly collaborative environment where their work will directly impact the research and trading process.
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