Jan Schüler
Financial Software Engineer
Freelancer
Looking for Expertise in Financial Software & Data?
I specialize in building data-driven applications for the financial services sector, combining expertise in:
- Software Engineering
- Data Engineering & Analytics
- Financial Markets
With a strong grasp of both modern software practices and financial markets, I help you optimize workflows, enhance user experience, and ensure your financial applications are smooth, reliable, and maintainable.
Let’s discuss your project needs. Feel free to get in touch.
Services
- Web Applications
- Backend Development
- Web APIs & Microservices
- Cloud Migration Support
- Test & Process Automation
- System & Code Refactoring
- Data Modeling & Architecture
- Data Integration & Pipelines
- Data Automation & Orchestration
- Data Quality
- Data Analysis & Visualization
- Data Migration
- Quantitative Finance Applications
- Market Data Systems
- Portfolio Analytics
- Market & Counterparty Risk
- Regulatory Compliance Tools
- QuantLib Integration
Skills
Python, C++, SQL, Pytest, Git
Pandas, NumPy, Pydantic, Bokeh, Plotly, QuantLib
FastAPI, Flask, Panel, Dash, OpenAPI
Oracle, PostgreSQL, Microsoft SQL Server, Snowflake
Jenkins, Airflow, AWS, Grafana, Datadog, Splunk, systemd, Jira
Clean Coding, Design Patterns, Requirements Engineering, System Analysis
Experience
Key Achievements
- Developed an web app for interactive yield curve modeling and visualization, streamlining daily QA and ad-hoc analysis.
- Implemented a process scheduling and orchestration solution, built CI/CD pipelines, enhancing deployment and infrastructure reliability.
Business Domain
- Quantitative yield curve modeling for bond portfolio valuation.
Technologies
- Python, Panel, Jenkins, Airflow, Pandas, Bokeh, QuantLib, C++, Oracle
Key Achievements
- Refactored and migrated energy forecasting systems to the cloud, improving availability and scalability while reducing operational overhead.
- Developed connector libraries and API interfaces for seamless trading data integration, simplifying efficient data access and utilization.
Business Domain
- Quantitative forecasting of renewable energy production for energy trading operations.
Technologies
- Python, Pandas, FastAPI, AWS, Snowflake, PostgreSQL
Key Achievements
- Built web APIs for quantitative finance applications, facilitating the migration to cloud infrastructure.
- Modernized legacy codebases, implemented test automation, and created comprehensive API documentation.
Business Domain
- Quantitative valuation of derivatives and bonds, including climate stress testing for portfolio risk assessment.
Technologies
- Python, C++, FastAPI, Flask, Azure, Oracle, QuantLib
Key Achievements
- Implemented a process scheduling solution to orchestrate and monitor end-to-end market data flows from vendors to clients.
- Conducted large-scale data migrations from a legacy market data system to a new platform, ensuring a smooth system transition.
- Performed data analysis, visualization, and automation projects, delivering operational insights.
Business Domain
- Launch of a comprehensive market data system for multiple asset managers, ensuring data quality and availability.
Technologies
- Python, Pandas, Dash, JobScheduler, Oracle, SQL Server, PostgreSQL
Key Achievements
- Developed and optimized quantitative models for derivatives pricing, including exotic options.
- Automated a counterparty risk analytics system, significantly reducing manual intervention and errors.
Business Domain
- Derivatives pricing, counterparty credit risk, and collateral management.
Technologies
- C++, QuantLib, Oracle, PL/SQL, Python
Key Achievements
- Developed data warehouse solutions for investment fund performance and risk reporting.
- Integrated diverse data sources and automated quality assurance, improving reporting accuracy.
Business Domain
- Factsheet reporting for investment funds.
Technologies
- Oracle, PL/SQL, Informatica Powercenter
Certifications
