ID251746 (Junior) Consultant – Financial Risk Management

• GCA Family & Sub-family: Consulting – Risk, Regulatory & Compliance Advisory Services
• Career Level: Level 6 – Team Member 1

You will be part of the Financial Risk Management team, supporting advisory and audit-related projects where we help clients build, validate and calibrate credit risk models, as well as review key areas of their risk frameworks.

• →Support risk model development & validation
  Assist senior team members in developing and validating credit, market and liquidity-risk models (e.g. IFRS 9, IRRBB, stress testing, rating & scoring).
  Contribute to quantitative analyses that test model performance, stability and regulatory compliance.
• →Data analysis & prototyping
  Work with large financial datasets: clean, transform and explore data to identify patterns, trends and risk drivers.
  Run statistical tests and build analytical prototypes in Python or R, leveraging forecasting techniques, machine learning and, where relevant, text mining.
• →ESG-risk analytics & process automation
  Support ESG-related risk analytics, helping to integrate sustainability and climate-risk considerations into quantitative frameworks.
  Assist in building scripts and tools to automate data processing and reporting, contributing to more efficient and reproducible workflows.
• →Documentation & client deliverables
  Draft sections of technical reports, including methodology descriptions, analysis results and model validation findings.
  Help prepare client presentations, dashboards and visualizations that clearly communicate key insights and recommendations.
• →Research & methodology enhancement
  Bring in knowledge from your master’s/university projects (e.g. econometrics, ML, risk modelling, text mining) to strengthen our modelling approaches.
  Conduct targeted research on new techniques or regulatory developments and share findings with the team to support continuous improvement.
• →Collaboration & stakeholder interaction
  Collaborate with colleagues in Audit and Advisory to support integrated risk and regulatory projects.
  Help maintain strong working relationships with client personnel by being responsive, professional and curious about their business challenges.

You are at the start of your consulting career, with a solid quantitative background and a strong interest in applying data science, forecasting and machine learning to real-world risk and regulatory problems in the financial sector.

• Analytical & structured: You enjoy working with data, breaking down complex problems and building logical, quantitative solutions.
• Curious & eager to learn: You follow new developments in statistics, econometrics, ML or financial analytics and want to apply them in practice.
• Proactive & reliable: You take ownership of your tasks, pay attention to detail and deliver on commitments.
• Collaborative team player: You like working in teams, are open to feedback and share your knowledge with peers.
• Client-oriented: You are interested in understanding how banks and financial institutions work and in helping them improve their risk practices.

• Master’s or Bachelor’s degree in Finance, Economics, Mathematics, Statistics, Computer Science or a similar quantitative field.
• Demonstrated coursework or academic projects in risk modelling, econometrics, machine learning or financial analytics.
• Solid foundation in probability, statistics and financial-modelling principles (e.g. regression, time-series, classification, scoring).

• Working knowledge of Python or R for data analysis
• Ability to work with datasets: importing, cleaning, transforming and visualizing data.
• Basic understanding of how credit, market or liquidity risk is measured and modelled in financial institutions.

• Good written and spoken English; any additional language is a plus.
• Able to explain quantitative concepts in clear, structured language to colleagues who may not be specialists in statistics or coding.

• Internship or work experience in banking, fintech or consulting.
• Familiarity with SQL, SAS or VBA.
• Participation in case competitions, research papers or student conferences.
• Progress toward CFA, FRM or another professional certification in finance or risk management.

• Quantitative analysis and statistical/econometric thinking.
• Basic risk model development and validation support (credit, market, liquidity).
• Data manipulation, exploratory analysis and prototyping in Python or R.
• Problem-solving and critical thinking.
• Documentation, report writing and presentation support.
• Teamwork, collaboration and willingness to learn from senior mentors.