Quantitative Risk Graduate Programme 2025
Details
Quantitative Risk Graduate Programme 2025 (PWC240313-2) - PwC
Closing Date 2024/04/07
Reference Number PWC240313-2
Opportunity Quantitative Risk Graduate Programme 2025
Intake year 2025
Contract Type Fixed Term
Location - Country South Africa
Location - Office Cape Town, Johannesburg
Overview
Our strategy, The New Equation, is about how PwC brings together unique combinations of people, powered by technology, galvanizing ourselves as a community of solvers to address those dual challenges. The foundation of the strategy is our multidisciplinary model, which allows us to help clients build trust and deliver sustained outcomes by bringing together deep expertise across a broad range of capabilities. It is this combination of capabilities and the ability to look at things from different perspectives that is so essential to delivering high quality and real impact for clients, stakeholders and society at large in Africa and globally.
Actuarial, Risk & Quants (ARQ) is a global team within PwC that provides cutting-edge actuarial, quantitative risk and financial consulting services to a wide range of clients. PwC offers a flexible and dynamic work environment that exposes you to an elite global network of actuarial and quantitative risk management experts. During your career with us you’ll get to work with a young, driven, supportive team in a fun, friendly and professional environment. You can expect excellent mentorship, stretch assignments and international exposure early in your career. You’ll be working on a variety of projects across a range of industries, covering valuations and banking exposure.
Requirements
We’re looking for full-time South African students who are currently enrolled at an accredited tertiary institution and are in their ultimate year of their Quantitative degree (includes Honours and/or Masters).
The following degrees will be considered:
Financial Modeling
Financial Engineering
Mathematical Finance
Mathematics
Quantitative Risk Management
Actuarial Science
Mathematical Statistics
Technical knowledge of programming languages like SAS, VBA, Python and Matlab is an advantage.
Comments