Investment Data Consultant

Salary: Not Specified

Location: London, England, United Kingdom

Job Type: Full time

The Emerging Markets (EM) team runs over £20 billion in emerging markets equities. The team targets alpha generation using a structured country allocation process and fundamental bottom up research.   The Data Insights Unit (DIU) is a team of data scientists which supports investors throughout

The Emerging Markets (EM) team runs over £20 billion in emerging markets equities. The team targets alpha generation using a structured country allocation process and fundamental bottom up research.


 


The Data Insights Unit (DIU) is a team of data scientists which supports investors throughout Schroders, and has been instrumental in deploying modern data science technologies and methods throughout the firm.


 


The opportunity exists for a new role reporting directly to the EM Equity Strategist, as an associate member of the DIU. The successful applicant will act as the EM team’s data subject matter expert. They will collaborate with the EM investment analysts and portfolio managers to understand their needs, and propose and implement data-driven tools to support the development of investment ideas.


 


As an associate member of the DIU the applicant will participate in data science knowledge sharing, and both contribute to and draw upon the expertise of the broader Schroders community of data professionals.


 


The applicant will have a strong preference towards working in reproducible data workflow tools such as Jupyter and RMarkdown, but won’t be afraid of interacting with complex Excel/VBA models and legacy data systems. The applicant will take pleasure from finding simple solutions to complex problems.


Previous experience in the investment industry would be valuable, but is not required if the applicant can demonstrate a passion for understanding how businesses and markets operate.


 
Job Description


 


1) Propose and execute improvements to the EM team’s existing data-driven tools and processes.


2) Maintain a strong relationship between the EM team and the DIU, identifying opportunities to bring the DIU’s tools and datasets into the EM team’s processes.


 
Essentials:
 
• High proficiency in SQL and at least one of Python/R.
• Familiarity with Excel/VBA models.
• Experience implementing automated data processing and reporting tools.
• Communication and problem solving skills.
• Passion for building tools that help people to make better decisions.
• Relevant degree background, either computer science or a quantitative discipline.
 
Useful but not essential:
 
• Knowledge of information visualisation principles and/or user experience design.
• Experience in data engineering, technology consulting, business intelligence or operations research.
• Data Management, ETL, or DBA experience.
• Prior experience in an investment organisation, preferably with exposure to Factset, Bloomberg or other investment-specific data platforms.
• Some knowledge of mathematical modelling, statistical analysis, quantitative finance or general data science techniques.