Python Quant Developer

This is an excellent opportunity for a highly analytical developer with strong experience in Python-based trading and risk models, quantitative modelling, back-testing and production-grade software engineering within the financial industry.

Python Quant Developer

Job description:

As a Python Quant Developer, you will design, implement and maintain Python-based quantitative models for areas such as yield curve modelling, pricing, risk management and portfolio optimization. You will also contribute to the re-architecture and migration of an existing MATLAB application into Python.

Your main tasks will include:

• Designing, developing and maintaining Python-based quantitative models for trading, pricing, risk and portfolio management
• Migrating and re-architecting existing MATLAB applications into Python
• Developing and executing back-tests and stress tests to validate strategy performance across different market regimes
• Translating mathematical and quantitative models into clean, production-ready Python code
• Collaborating closely with quantitative researchers, traders, data engineers and analytics engineers
• Integrating models with market data, reference data and alternative data feeds
• Ensuring that data pipelines are robust, scalable and suitable for production use
• Optimizing Python code for performance, low latency and high throughput
• Implementing version control, CI/CD pipelines and automated testing frameworks
• Monitoring, maintaining and troubleshooting existing applications and production pipelines
• Proposing and applying best practices in quantitative finance, numerical methods and the Python ecosystem

About the customer:

For our client in the banking sector in Basel, we are looking for an experienced Python Quant Developer to join the Banking Technology team. In this role, you will work on software solutions supporting reserve managers and traders, with a strong focus on quantitative finance, Python development and the migration of existing MATLAB applications into Python.

Location: Basel, Switzerland

Workload: 100%

Start date: ASAP or within 3 months

Contract duration: 24 months, with likely extension

Requirements:

You are a strong Python developer with a background in quantitative finance, statistical modelling and financial applications. You enjoy working at the intersection of software engineering, financial markets and mathematical modelling.

• Around 5 years of experience as a Quant Developer, Quantitative Analyst or in a similar role with a focus on Python-based implementation of trading or risk models
• Strong proficiency in Python and relevant libraries such as NumPy, Pandas, SciPy, statsmodels, prophet, Darts and QuantLib
• Experience developing and back-testing trading strategies using frameworks such as Zipline, Backtrader or custom back-testing solutions
• Strong understanding of financial instruments such as equities, fixed income and derivatives
• Good knowledge of quantitative techniques such as Time Series Analysis and Monte Carlo simulation
• Proven experience developing Python applications in the financial industry
• Basic understanding of MATLAB code, ideally with experience translating MATLAB logic into Python

Nice to have:

• Bachelor's or Master's degree in quantitative finance, mathematics, physics, computer science or a related field; PhD is a plus
• Experience with Python data application frameworks such as Streamlit, Plotly Dash or Panel / HoloViz
• Solid understanding of term structure of interest rates, yield curve construction and calibration techniques such as bootstrapping and spline fitting
• Familiarity with models such as Vasicek, CIR, Hull-White, Nelson-Siegel and Svensson
• Experience packaging Python applications as self-contained deployable binaries
• Familiarity with cloud platforms such as Azure or AWS
• Experience with containerization technologies such as Docker
• Experience with back-end frameworks such as Flask, Django or FastAPI
• Strong experience with data manipulation, SQL and NoSQL databases
• Certifications in quantitative finance, such as CQF, or recognized data science certifications

Compensation benefits:

• A long-term project in a highly professional banking environment
• Work on business-critical applications used by reserve managers and traders
• A technically challenging role combining Python, quantitative finance and production software engineering
• Close collaboration with experts from Banking Technology, Data & Analytics and Asset Management
• 24-month contract with likely extension

You are a strong Python developer with a background in quantitative finance, statistical modelling and financial applications. You enjoy working at the intersection of software engineering, financial markets and mathematical modelling.

• Around 5 years of experience as a Quant Developer, Quantitative Analyst or in a similar role with a focus on Python-based implementation of trading or risk models
• Strong proficiency in Python and relevant libraries such as NumPy, Pandas, SciPy, statsmodels, prophet, Darts and QuantLib
• Experience developing and back-testing trading strategies using frameworks such as Zipline, Backtrader or custom back-testing solutions
• Strong understanding of financial instruments such as equities, fixed income and derivatives
• Good knowledge of quantitative techniques such as Time Series Analysis and Monte Carlo simulation
• Proven experience developing Python applications in the financial industry
• Basic understanding of MATLAB code, ideally with experience translating MATLAB logic into Python, * Bachelor's or Master's degree in quantitative finance, mathematics, physics, computer science or a related field; PhD is a plus
• Experience with Python data application frameworks such as Streamlit, Plotly Dash or Panel / HoloViz
• Solid understanding of term structure of interest rates, yield curve construction and calibration techniques such as bootstrapping and spline fitting
• Familiarity with models such as Vasicek, CIR, Hull-White, Nelson-Siegel and Svensson
• Experience packaging Python applications as self-contained deployable binaries
• Familiarity with cloud platforms such as Azure or AWS
• Experience with containerization technologies such as Docker
• Experience with back-end frameworks such as Flask, Django or FastAPI
• Strong experience with data manipulation, SQL and NoSQL databases
• Certifications in quantitative finance, such as CQF, or recognized data science certifications