Job Description

Company Description

Building the bank of tomorrow takes more than skills.

It means combining our differences to imagine, discuss, code, develop, test, learn... and celebrate every step together. Share our vibes? Join Swissquote to unleash your potential.


We are the Swiss Leader in Online Banking and we provide trading, investing and banking services to +500'000 clients, through our performant and secured digital platforms.


Our +1000 employees work in a flexible way, without dress code and in multicultural teams.

By having a huge impact on the industry, they are growing their skills portfolio and boosting their career in a fast-pace environment.


We are all in at Swissquote. As an equal opportunity employer, we welcome candidates from all backgrounds, experiences and perspectives to join our team and contribute to our shared success.


Are you all in? Don't be shy, apply!

You will join the FX & DA Trading department, which serves the bank's electronic trading business acting as principal counterparty in OTC venues and CLOBs, and particularly the SPOT liquidity team.


As a team we:

contribute to the bank's commercial goals by managing our in-house developed internalization system provision liquidity such that clients' execution needs and the bank's regulatory requirements are sustainably met drive the bank's ongoing investments in its proprietary trading and risk systems in collaboration with software engineers and IT drive the quantitative research initiatives relevant to its business scope ensure excellent product quality and participate in its continuous improvement

You will play a primary role in implementing the team's quantitative research roadmap and will have the chance to participate in shaping it. The goal is sell-side systematic trading and pricing strategies valid for production. In this context, you may work in collaboration with quants of other teams and a consulting professor with academic experience in market microstructure.


Moreover, the role includes ad hoc data exploration/visualization and reporting to address Traders' needs.

Qualifications

PhD/MSc in a STEM discipline from top ranked university Strong analytical and modelling skills suitable to financial tick-data Familiar with Machine Learning methods applied to financial forecasting Strong coding skills, especially with respect to Python packages relevant to large data-sets Previous experience with a sell-side electronic trading firm/bank is a strong plus Able to work under pressure and available to deliver on time Self-driven, structured, attention to detail, team-oriented Excellent communication skills and able to develop relationships with interdisciplinary people Fluent in English

Additional Information