Senior Quantitative Developer (f/m/d) Zurich

LGT is the world’s largest family-owned and managed Private Banking and Asset Management Group. For more than 100 years it has been fully owned and managed by the Princely House of Liechtenstein, which is also one of our biggest clients.
With around 800 employees, LGT Bank Switzerland has established itself as a renowned Swiss private bank and is an excellent address for both wealthy private clients and employees - this was also confirmed last year by the independent institute "Great Place To Work", which awarded LGT Bank Switzerland the title of one of the best employers in Switzerland.

• Implementation and Production: Implement, deploy, and maintain quantitative models for portfolio construction, risk, factor analytics, and systematic strategies in production.

• System Architecture and Engineering: Design and maintain scalable Python infrastructure for backtesting, optimisation, and live analytics, with strong testing and CI/CD practices.

• Quantitative Methods: Translate research methodology into production systems — portfolio optimisation, factor risk models, covariance estimation — using libraries such as CVXPY or Mosek.

• Collaboration and Delivery: Work with portfolio managers, researchers, and IT to translate research designs into deployable production-quality code.

• Continuous Improvement: Maintain and improve the team's analytical infrastructure and engineering practices; stay current with relevant developments.

• Educational Background: Master's or PhD in a quantitative field (Computer Science, Mathematics, Statistics, Engineering, Physics, Finance, or related).

• Professional Experience: 5+ years in quantitative developer or research engineer roles at a buy-side asset manager, hedge fund, QIS desk, or specialist quant vendor. Production experience implementing portfolio construction, risk, or factor models is mandatory.

• Technical Skills (Required): Expert Python with production engineering discipline (packaging, testing, CI/CD); NumPy, pandas; optimisation packages (CVXPY, Mosek, SCIP); SQL; Git.

• Technical Skills (Preferred): Compiled languages (C++, Rust, Java), cloud platforms (Azure, AWS, GCP), ML frameworks, or container technologies.

• Domain Knowledge: Portfolio theory, factor models, risk measures (VaR, ES, tracking error), and multi-asset instruments.

• Track Record: Proven ability to deliver and operate production-quality quantitative systems in cross-functional teams.

• Personal Qualities: Hands-on builder mindset, attention to detail, and effective communication with technical and non-technical stakeholders.

• Languages: Fluent English required; German is an asset.

Please note that we cannot consider applications via recruitment agencies for this position.