Analyst Consultant - Risk Analytics

Key Skills

AI technology, Anomaly detection, Deep Learning, Effective communication skills, English Proficiency, Graph analytics, Ignite, Machine learning techniques, MATLAB Programming, MongoDB, Natural Language Processing (NLP), NoSQL, Python Programming, Quantitative models, R Programming, SAS, SQL

Job Description

WHO YOU'LL WORK WITH

You’ll join our global Risk & Resilience Practice in one of our European offices and be part of the Risk Analytics team. 

Risk Analytics is the tech-enablement power engine of Risk & Resilience. We combine deep analytical and technical expertise with distinctive strategy and transformation capabilities to support clients in everything - from large-scale analytics programs to in-depth technical modelling exercises.

We develop and deploy leading-edge solutions incorporating the latest innovations in methodology and technology and maintain in-depth knowledge of regulatory developments. We convene leaders in the industry to build and share knowledge to drive long-term sustainable change in the practice of risk data and analytics.

We have over 18 years of expertise serving leading institutions across industries in the fields of model development, model advisory, model validation, and model risk management.

We are a diverse global community of world-class practitioners with a shared passion to build risk analytics capabilities that break new ground, transform industries, and shape markets. We solve real life business problems for our clients; work with us and you will learn from the best and have your voice heard from day one.

There is flexibility to hire at the Analyst or Senior Analyst level depending on candidate experience.

WHAT YOU'LL DO

As an Analyst Consultant in Risk Analytics, you will:

• Help clients to develop, refine and review their models using cutting-edge technology to better manage risk, assess market opportunities and create business benefits, across different areas of expertise.
• Assess our clients’ frameworks for model development and risk management across a variety of risk topics. This includes credit risk, market and trading risk, climate risk, financial crime and compliance and wider applications such as cyber and digital trust.
• Analyze content and data, identify risk vectors, build prototypes, interpret results, find new solutions, derive conclusions, support clients to implement recommendations, and enjoy solving problems that focus on adding business value.
• Be expected to communicate complex analytics concepts in a clear and concise manner to key client stakeholders  
• Be able to establish connections between sophisticated modelling techniques and strategic decision-making processes. You will have exposure to a highly international environment as our client base is global  
• Work on projects and exchange experiences with your colleagues which means you will face new intellectual challenges daily, while continuously building your methodological knowledge and skills, as well as your strategic consultancy toolkit 

QUALIFICATIONS

• Bachelor’s degree required. Advanced quantitative degree (Masters or Ph.D. in computer science, mathematics/statistics, engineering, or financial engineering) would be a plus
• 2+ years of relevant experience in quantitative analysis/modelling to solve real world problems   
• Experience across model lifecycle, including active participation in activities of development, implementation and/or testing of risk models (vendor or “in-house” models)  
• First experience in programming (beyond simple scripts) in a modern scientific language (e.g., Python, Matlab, R). Knowledge of SQL, NoSQL (e.g. MongoDB, Ignite) and SAS would be a strong plus  
• Experience in one of the following machine learning / AI areas: natural language processing, deep learning, anomaly detection, graph-based techniques would be a strong plus  
• Ability to work collaboratively in a team environment and effectively with people at all levels in an organization  
• Exceptional communication skills - especially around translating technical knowledge into forms that can be digested by leadership and non-technical project teams-, verbally and in writing, in English and the local office language(s)  
• Willingness to travel