UBS Financial Services Algo Quant Analyst in London, United Kingdom

Your role:

Are you capable of making sense of large amounts of noisy data, presenting your quantitative findings in succinct human understandable form? If so we are looking for someone who can:

  • Work with sets of unstructured, often dirty / incomplete data.

  • Work with large datasets of high frequency market and trade client data

  • Extract meaningful information from these datasets.

  • Explain and communicate such information to both internal colleagues and external clients clearly and succinctly in both verbal and written forms.

  • Work individually and within a group of market researchers and quantitative developers;

What we offer:

Together. That’s how we do things. We offer people around the world a supportive, challenging and diverse working environment. We value your passion and commitment, and reward your performance.

Keen to achieve the work-life agility that you desire? We're open to discussing how this could work for you (and us).

Take the next step:

Are you truly collaborative? Succeeding at UBS means respecting, understanding and trusting colleagues and clients. Challenging others and being challenged in return. Being passionate about what you do. Driving yourself forward, always wanting to do things the right way. Does that sound like you? Then you have the right stuff to join us. Apply now.

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.

Your team:

You’ll be working in the Front Office Algo Trading Electronic Execution team in London, a recently formed global business within UBS dedicated to innovation in cross-asset electronic execution services.

Our role is to provide corporate, institutional and wealth management clients with electronic execution capabilities across the world’s capital markets.

Within the team we combine knowledge of market microstructure and order execution data with analytical, econometric, machine learning and computer simulation techniques applied to large amounts of data to build modern execution trading algorithms and to provide our clients with the supporting tools required to choose, monitor and evaluate the strategies they select. We conceptualize new algorithms and evolve to bring them into full production and provide guidance and support for our clients to execute their algo orders.

Your expertise:

  • Degree in applied mathematics or hard sciences.

  • Experience of data analysis especially with unstructured and dirty data sets together with a good grasp of statistics and probability.

  • Software development experience especially in python including the common data handling and analytics libraries (pandas, numpy, scipy etc).

  • Experience with linux and software development control systems and associated good practice.

  • Experience with electronic trading in capital markets (is to be desired but not essential).

  • Highly motivated by opportunities in the field of data analysis.

  • Self-motivated in problem-solving.

  • Able to coordinate and organize work on several projects simultaneously.

  • Attracted to work in the team combining your strength with complementary skills from similar minded professionals in the field of electronic trading..

  • Fully committed to do best for our clients when developing general trading methodologies and customizing them for individual clients.

*LI-DNI

About us:

Expert advice. Wealth management. Investment banking. Asset management. Retail banking in Switzerland. And all the support functions. That's what we do. And we do it for private and institutional clients as well as corporations around the world.

We are about 60,000 employees in all major financial centers, in more than 50 countries. Do you want to be one of us?

Your colleagues:

Job Reference #: 183867BR

Business Divisions: Investment Bank

Title: Algo Quant Analyst

City: London

Job Type: Full Time

Country / State: United Kingdom

Function Category: Quantitative Analysis