The Commission is recruiting for a Data Scientist to assist the Risk and Operations Division with a project under our three year business plan. This is a fixed-term temporary position for c. 18 months.
The aim of the Quant III Project is to utilise new and useful technology to improve the efficiency and effectiveness of our authorisations process. During 2023, we spent a considerable amount of effort thinking about our current applications and authorisations process, re-imagining it and designing a new, digitalised system to facilitate it underpinned by modern technology. Throughout 2024, we plan to develop this system and create a new applications portal that will revolutionise the submission and authorisation process for applications. Currently, firms and applicants must download and complete a form in Microsoft Word before emailing it, along with attachments, to the Commission for assessment. The new system, due to launch in 2025, will enable firms and those wanting to do business in the Bailiwick to complete these forms online, with guardrails in place to improve the quality and completeness of submissions. The portal will support online collaboration and communication throughout the application process, between parties drafting an application before submission, and with the Commission post-submission.
The main duties and responsibilities of the role will include:
- Providing support on the development and implementation of a more analytics-led approach to the risk-based supervision of our licensees.
- Liaising with divisional representatives in order to identify, develop, create and test innovative tools to further enhance and augment the Commission’s approach to risk-based supervision.
- Preparing and presenting findings, demonstrations and training to a range of stakeholders across the Commission, including at project board meetings.
- Takes responsibility for querying and analysing data from relational databases and understanding data quality, data models, data dictionaries and data taxonomies.
- Using a range of Machine Learning techniques (both supervised and unsupervised learning), Natural Language Processing, Optimisation and Cognitive Computing solutions to solve problems.
- Analysing and interpreting complex digital data to discover knowledge and assist decision making.
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