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Algo Model Validation Quantitative Analyst

Id Job: 316e784

🏠 On-site
💼 UBS
📍 London, England
1 day ago
💰 65000 – 100000 GBP ANNUAL

Job Description

United Kingdom
Risk
Group Functions

Job Reference #

273137BR

City

London

Job Type

Full Time

Your role

Are you someone with a passion for market dynamics and quantitative analysis? Are you someone who likes a challenge and is willing to explore an emerging area of Risk Control in Algorithmic trading models? Are you a team-player, blending quantitative analysis with risk analysis to ensure best in class Algo model risk management is achieved in an efficient and compliant manner? We are looking for an Algo Model Validation Quantitative Analyst like you to:

  • contribute to the model validation practices of our electronic trading algos and perform independent reviews/validations
  • provide an expert assessment of the testing frameworks for electronic trading algos, ensuring that new and changed algos will not have an adverse impact on the markets, our clients and UBS
  • contribute to the monitoring of the performance of trading algorithms versus their intended aims
  • become a subject matter expert on assessing the design and performance of algos

Your team

You will be part of our Model Risk Management & Control (MRMC) Risk Models function in London on a permanent basis and work closely with electronic trading stakeholders including Quants, IT Developers and Traders as well as other control functions.

Our mandate is to conduct quantitative analysis of risk associated with electronic trading algos. This includes independent quantitative testing, integration with FX/Equities trading systems, developing benchmark models/algos and front-to-back governance activities.

Diversity helps us grow, together. That’s why we are committed to fostering and advancing diversity, equity, and inclusion. It strengthens our business and brings value to our clients.

Your expertise

  • a degree in Mathematics, Physics, Engineering, Computer Science, Statistics, Data Science, or Financial Engineering
  • proven FX, Fixed Income or Equities product knowledge
  • proficiency in Python coding and other general purpose programming languages (preferably Java)
  • knowledge of Linux, command line, SQL and Q is a strong plus
  • an understanding of algo/e-trading models from a quantitative development, technology, trading or model validation perspective
  • strong written and verbal communication skills and the ability to explain highly technical topics clearly
  • familiarity with data assembling and analysis, computational statistics or machine learning techniques
  • knowledge of pricing models, risk models or stochastic calculus will be of added value
  • experience in a Front Office role is a plus.

About us

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?

Join 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.


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