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EY FAAS Quants Manager 
Zimbabwe, Harare, Harare 
367203259

26.08.2025

Your key responsibilities:

  • Collaborate with the Senior Manager and the Partner to execute a FAAS strategy that satisfies high client expectations, support the planning, execution and delivery of the engagements
  • Contribute actively in the FAAS engagement team to understand and respond to the client's needs and expectations and develop a client-focused, clear, accurate and well-presented work product
  • Ensure work is delivered in a timely manner and in compliance with EY high standard requirements
  • Work with other service lines and subject matter experts in providing an integrated service delivery across functions in an international team to meet the client high expectations.
  • Identify and communicate relevant trends, developments and key performance drivers relevant to the client and its industry.
  • Assist in developing new opportunities related to new FAAS projects and relationships.

Skills And Attributes for Success

  • Strong analytical, problem solving and critical thinking skills
  • Willingness to learn and continuously expand technical and business skills
  • Ability to understand, produce and communicate complex/technical ideas to a non-technical audience
  • Sound business, client, team and personal leadership skills including verbal communication and presentation skills
  • Excellent interpersonal skills and ability to work effectively within a team
  • Solid project management skills
  • Team management skills
  • Willingness and ability to travel and work abroad for international projects

To qualify for the role, you must have

  • Excellent academic background, including a Bachelor and a Master’s in Mathematics, Statistics, , Financial Engineering, Financial Mathematics, Actuarial Science, Operational Research, Econometrics, Data Science, Economics, Finance, Risk Management or other related field with strong quantitative focus. Ph.D. will be considered an asset.
  • A professional qualification in PRM, FRM, ERM, CQF, Actuarial Qualification or progression towards attainment of the same.
  • At least 3-5 years’ experience in risk management

Professional experience with focus on one or more of the following:

  • Quantitative techniques and analytics in various areas within credit risk
  • Model development, validation and implementation across credit risk quantification purposes (i.e. PD/LGD/CCF estimation, decision-making, stress testing)
  • Knowledge of credit risk related regulatory requirements (e.g. IFRS 9, IRB, Stress Testing, Early Warning, Climate and ESG risk incorporation in Credit Risk)
  • Knowledge of risk-related regulatory landscape and requirements
  • Basel II/III implementation.
  • Data management, mining, cleansing and visualization with application on credit risk data
  • Strong skills in programming and quantitative analysis packages (e.g., Python, R, SAS, SPSS) or/and data management (e.g., SQL)
  • Credit policies and processes, credit risk data and related financial institutions’ internal and external requirements.
  • Experience in the design and implementation of credit risk model related frameworks (model lifecycle management, development, validation, implementation).

Ideally, you’ll also have

  • Experience in data analysis, data quality, data automation and data management including familiarity with Big Data technologies
  • Solid understanding of advanced statistical, Artificial Intelligence and Machine Learning techniques for classification, clustering and forecasting and hands-on experience using programming languages such as Python
  • Experience in working on cloud technologies (e.g., MS Azure, Databricks)
  • Experience in the design and implementation of credit risk model related frameworks (model lifecycle management, development, validation, deployment)
  • Understanding of the credit lifecycle and credit processes (origination, approval, monitoring, workout, and collections)
  • Knowledge of climate and other environmental, social and governance risks and their incorporation into credit decisioning and stress testing