Financial Services Quantitative Analyst Internship
Oliver Wyman are leaders in the consulting industry, advising the senior leadership of global corporations and institutions on their most complex and strategic issues. We advise governments, regulators, and non-profits on strategy, public policy and market structure.
Clients hire us for our depth of insight and expertise; expertise that comes from greater specialisation than our peers. We combine analytical rigour with a relentless focus on changes that will improve our client’s performance.
The Financial Services Quantitative Analysis (FSQA) team is a new business unit, set up in 2017 in Newcastle to focus on helping our clients solve quantitative problems. We are a small, dynamic team of quantitative analytics specialists. Our clients are the leading financial institutions across the world. Our core work is building and validating finance and risk models.
For this internship you will be based in the Financial Services Quantitative Analysis office in central Newcastle. You will work as part of our small, fast-growing team to build a new model for our modelling library. You will have ownership of the model from start to finish, starting with model design taking it all the way to client-ready release. You will be provided with self-directed training resources and receive one-to-one support from your internship supervisor to develop your modelling approach and Python coding skills.
We are looking for candidates from quantitative disciplines, including: Maths, Physics, Engineering, Computer Science, Economics
We are looking for someone who is excited to work as part of a small team in a start-up/entrepreneurial environment, who enjoys working autonomously and is focused on delivering output.
A good working knowledge of Microsoft Excel and some programming experience would be beneficial e.g. Python, R, MatLab. Python training and support will be provided during the internship.
- Research and Develop understanding of what the model needs to do
- Build a prototype model in Python, validate and calibrate model
- Refine the model ready for release into the Oliver Wyman model library, complete robust documentation to communicate how the model works