Quantitative Data Engineer / Data Scientist

Universities Superannuation Scheme Limited
London, United Kingdom
Competitive plus Bonus/Benefits
10 May 2022
09 Jun 2022
Job Function
Industry Sector
Finance - General
Employment Type
Full Time
Key Responsibilities
  • Work with other front office equities and credit investment teams to define areas of research and relevant datasets to analyze and onboard.
  • Work with the Investment and Market Systems (IMS) and End-User Computing (EUC) teams on the development of, and our interface to, our enterprise data management platform.
  • Define and own equity-related data architecture that is not centrally managed by the IMS team.
  • Build and manage data pipelines to extract and cleanse raw data and archive into a high-performance production environment to be used for quantitative research.
  • Assist in the development of an internal quantitative research platform and associated APIs.
  • Write effective documentation and research reports communicating complex quantitative topics and relationships effectively to non-technical stakeholders.

Technical Competencies, Skills and Experience

Key Competencies:
  • Professional experience of statistical modelling of time series data, ideally financial and with a STEM degree with post-graduate research in the field.
  • Expert knowledge of data architecture and storage, ideally SQL Server, as well as advanced Python skills with experience of writing and deploying production-level code.
  • Have opinions on database best practice and associated technologies such as ORMs.
  • Experience supporting quantitative research tools such as backtesting engines, returns analysis frameworks, optimization tools and machine learning models.
  • Experience of Python data analysis libraries such as Pandas, NumPy, SciPy, Scikit-learn, etc.
  • Experienced writing technical documentation and using version control frameworks such as Git.

General Skills and Experience:
  • Ability to think independently and own technical decisions.
  • Fast learner with a natural curiosity of new technologies and approaches.
  • Excellent data communication skills, written or verbal.
  • Strong compliance culture and high personal ethical standards.

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