Cambridge Suptech Lab Internship

Overview

This internship suits people with different profiles who have experience in academic research, supervision, data science, technology, project management or consulting, as well as those who are interested in digital transformation solutions.

Duration:
3-6 months

Time commitment:
20-40 hours per week

Format:
Online/remote

The programme

The Cambridge SupTech Lab is empowering a community of ‘Innovation Leaders’ via digital tools and executive education to develop cutting-edge suptech applications. In our vision, effective digital supervision and regulation enables sustainable delivery of innovative financial services, greater protection of consumers, and the pursuit of other policy objectives such as financial integrity and the oversight and mitigation of environmental and governance risks.

This customisable internship programme allows for a unique and dynamic exploration of suptech innovations and the digital transformation of supervisory agencies, providing the opportunity to influence the new shape of financial supervision.

The Cambridge SupTech Lab Internship is remote and open to applicants from any geographical location.

The role

This internship suits people with different profiles who have experience in academic research, supervision, data science, technology, project management or consulting.

Main responsibilities

Your main responsibilities may include a combination of:

conducting original research at the frontier of financial supervision
Scoping and summarising of literature (including academic, supervisory, and industry-specific publications)
analysing suptech use cases and applications
developing frameworks for future curricula
participating in data mapping exercises
manage the development of digital tools for supervisory authorities
engaging with specific parts of the data and literature and co-authoring reports with our core team
participating in dissemination of findings or publications.

Benefits

As an intern you:

will have a real impact, contributing to shape more resilient, inclusive, and sustainable financial sectors
will gain practical research experience and insights into the inner workings of a leading innovation lab
may be offered financial reimbursement for expenses (relative to your personal circumstances up to £800/month in case of full-time commitment and £400/month for part-time)
will work with world-leading experts, and have access to the knowledge sharing sessions with peers and experts from the Cambridge Center for Alternative Finance (CCAF)
might be invited to be co-authors of research reports
will receive a certificate upon successful completion of the internship programme to accelerate your career in digital assets by enhancing your CV.

About you

We are a diverse team, which a range of expertise and capabilities. We value a combination of the following qualities, skills and attributes.

In addition to our simple application form you are asked to provide a CV and cover letter demonstrating how your own experience meets these requirements.

Essential characteristics

• Experience in fintech, financial services regulation or supervision, or data science or consulting.
• Direct experience of working with/for a financial regulator/central bank/relevant authority.
• Masters or PhD with a background preferably in law, finance, economics, social sciences, data science, computer science or engineering.
• Driven and committed, demonstrating initiative, self-motivation, and eagerness to familiarise with new concepts.
• Excellent time management and planning skills with a commitment to deliver and being held accountable.
• Ability to work independently as well as being part of an interdisciplinary team in a collaborative project.

Desirable characteristics

Experience in conducting desk research, content analysis, data curation, user experience, and stakeholder management.
Strong writing and communication skills (English)
Able to organise ideas logically and effectively, while clearly communicating those that are interesting and important to specific underlying research-related topics.
Statistical skills, including modelling and data analysis.