Quberesearchandtechnologies
Data Scientist - Market Data
London. Posted 6 months ago
The role
You will design and develop financial datasets to support systematic strategies and trading decisions. You will use Python and data engineering skills to build and own automated production pipelines for market, pricing, and reference data.
What you will do
- Collaborate with Quantitative Researchers and Traders to design financial datasets
- Develop Python code to extract, clean, normalise and aggregate data from financial market data sources
- Design, build and maintain automated data pipelines
- Develop and maintain pricing and reference datasets across financial instruments and markets
- Investigate and resolve data quality and production issues
- Evaluate and implement new approaches to data extraction, processing and onboarding
- Take ownership of production data workflows
Required qualifications
- 2 to 5 years of experience in a data focused role working with financial or market data
- Strong understanding of financial markets and instruments, including the behaviour and characteristics of pricing and reference datasets
- Advanced Python programming skills, including experience with data processing libraries such as Pandas or Polars
- Experience designing, building and maintaining automated production data pipelines
- Strong data analysis and problem solving skills
- Postgraduate degree in Mathematics, Physics, Engineering, Computer Science or another quantitative discipline
- Strong communication skills
- Ability to operate effectively as priorities, systems, projects and business requirements evolve
Nice to have
- Experience working with market data platforms and APIs from providers such as Bloomberg or LSEG, including products such as Datastream, DataScope Select, Real Time, BPIPE or Data License
Benefits
- Initiatives and programs to enable employees achieve a healthy work-life balance
About the company
Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager. It is a technology and data driven group implementing a scientific approach to investing.