Quantitative Data Engineer / Data Scientist
- Employer
- Universities Superannuation Scheme Limited
- Location
- London, United Kingdom
- Salary
- Competitive plus Bonus/Benefits
- Closing date
- May 28, 2022
View more
- Job Function
- Other
- Industry Sector
- Finance - General
- Employment Type
- Full Time
- Education
- Bachelors
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Key Responsibilities
Technical Competencies, Skills and Experience
Key Competencies:
General Skills and Experience:
- 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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