Economic research associate vacancies
Financial Conduct Authority (FCA)
Type: 2 x temporary Research Associates
Start Date: Mid-March 2017
Duration: 2-3 months
Rate: £180 per day (negotiable)
Interested candidates should email their CV to bdu@fca.org.uk and Liridona.Asllani@fca.org.uk before Friday 3rd March 2017.
The Behavioural Economics and Data Science Unit (BDU) at the Financial Conduct Authority (FCA) is offering two research associate positions to support ‘big data’ economic research projects with household finance microdata. BDU is led by Stefan Hunt (Head of BDU, PhD Harvard) and supports the FCA’s policy, competition, supervisory and enforcement functions by designing and executing high calibre original research.
The roles involve advanced data manipulation, preparing microdata for economic analysis and designing sensitivity analysis on our cloud-based servers. Suitable candidates should have obtained, or be in the process of obtaining, a master degree or PhD and have experience using R. The appropriate candidate will also have knowledge and experience of managing large datasets. Familiarity with R packages dplyr, tidyr, data table would give candidates an advantage. Candidates with strong experience of other coding software (e.g. MATLAB, SAS, STATA) would also be considered. Knowledge of financial markets is not essential.
These roles also offer an opportunity to work within the BDU at the FCA. BDU is a new initiative at the FCA and aims to apply modern theory and applications from behavioural economics and data science to solve contemporary economic problems and increase the FCA’s effectiveness in achieving its operational objectives. Current BDU research also includes large-scale randomized controlled trials in household finance and application of data mining and machine learning. The roles are based at the FCA’s offices in Canary Wharf, London.
These roles require the individual to work at least three days a week. Applicants are encouraged to indicate their availability in their application e-mail (e.g. X days per week).
Financial Conduct Authority (FCA)
Type: 2 x temporary Research Associates
Start Date: Mid-March 2017
Duration: 2-3 months
Rate: £180 per day (negotiable)
Interested candidates should email their CV to bdu@fca.org.uk and Liridona.Asllani@fca.org.uk before Friday 3rd March 2017.
The Behavioural Economics and Data Science Unit (BDU) at the Financial Conduct Authority (FCA) is offering two research associate positions to support ‘big data’ economic research projects with household finance microdata. BDU is led by Stefan Hunt (Head of BDU, PhD Harvard) and supports the FCA’s policy, competition, supervisory and enforcement functions by designing and executing high calibre original research.
The roles involve advanced data manipulation, preparing microdata for economic analysis and designing sensitivity analysis on our cloud-based servers. Suitable candidates should have obtained, or be in the process of obtaining, a master degree or PhD and have experience using R. The appropriate candidate will also have knowledge and experience of managing large datasets. Familiarity with R packages dplyr, tidyr, data table would give candidates an advantage. Candidates with strong experience of other coding software (e.g. MATLAB, SAS, STATA) would also be considered. Knowledge of financial markets is not essential.
These roles also offer an opportunity to work within the BDU at the FCA. BDU is a new initiative at the FCA and aims to apply modern theory and applications from behavioural economics and data science to solve contemporary economic problems and increase the FCA’s effectiveness in achieving its operational objectives. Current BDU research also includes large-scale randomized controlled trials in household finance and application of data mining and machine learning. The roles are based at the FCA’s offices in Canary Wharf, London.
These roles require the individual to work at least three days a week. Applicants are encouraged to indicate their availability in their application e-mail (e.g. X days per week).
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