Quantitative Analyst-Model Validation Specialist
Job Reference #
Are you an expert in data analytics? Do you enjoy understanding models and their background? Are you organized with an eye for detail? We're looking for someone like that to:
• review and challenge models used in operational risk management/Anti Money Laundering/Treasury/Accounting/Investment management/AI/ML
• assess the conceptual soundness and appropriateness of different models and perform related outcome, impact and benchmark analyses
• run analyses on implementations to assess their correctness and stability
• carry out and document independent model validation in line with regulatory
• requirements and internal standards
• interact and discuss with model users, developers, senior owners and governance bodies
• support regulatory exercises
You will be working in Model Risk Management & Control (US) function within the US Chief Risk Officer organization. Our role is to understand and assess the risks associated with the use of models throughout the firm. We focus on models used to monitor operational risks such as money laundering, rogue trading or market manipulations, as well as artificial intelligence models used across the bank. You are responsible for identifying corrective actions that promote model risk management process improvements and ensuring the timely remediation of identified issues. You will interface with key stakeholders, US regulators and internal audit to discuss justification and reasoning behind validation and review findings.
The role requires a mix of expertise in statistics, information technology and specialist knowledge in monitoring of compliance and the use of artificial intelligence within the banking industry. Ideally, you have skills and experience in these areas but an eagerness to further develop your existing expertise is more important.
• a Masters (MSc) or PhD degree in a quantitative field (e.g. computer science, statistics, mathematics, physics, engineering or economics)
•3+ years hands on experience in developing or validating statistical/mathematical models
• expertise in data assembling and analysis, computational statistics, anomaly detection or machine learning including relevant programming skills, for example in R, Python, C++
• expertise in SQL, i.e. for querying and manipulating large databases
• strong writing skills and a structured working style
• familiarity with the global financial industry and its compliance and operational risks
• able to explain technical concepts in simple terms to facilitate collaboration
• willing to create your own brand in the group and companywide
• skilled at constructive criticism (you have the human touch)
• motivated, well organized, and able to complete tasks independently to high quality standards and delivering to tight timelines
• fluency in English (written and oral)
UBS is the world’s largest and only truly global wealth manager. We operate through four business divisions: Global Wealth Management, Personal & Corporate Banking, Asset Management and the Investment Bank. Our global reach and the breadth of our expertise set us apart from our competitors.
With more than 70,000 employees, we have a presence in all major financial centers in more than 50 countries. Do you want to be one of us?
At UBS, we embrace flexible ways of working when the role permits. We offer different working arrangements like part-time, job-sharing and hybrid (office and home) working. Our purpose-led culture and global infrastructure help us connect, collaborate, and work together in agile ways to meet all our business needs.
From gaining new experiences in different roles to acquiring fresh knowledge and skills, we know that great work is never done alone. We know that it's our people, with their unique backgrounds, skills, experience levels and interests, who drive our ongoing success. Together we’re more than ourselves. Ready to be part of #teamUBS and make an impact?
Disclaimer / Policy Statements
UBS is an Equal Opportunity Employer. We respect and seek to empower each individual and support the diverse cultures, perspectives, skills and experiences within our workforce.