Daniel Stahl
Verified Expert in Engineering
Mathematical Finance Developer
Birmingham, AL, United States
Toptal member since August 25, 2021
Daniel is a full-stack developer with nine years of real-world experience in financial modeling and analytics and three years of experience developing big data applications in Spark and Hadoop. He currently leads a machine learning operations team that designs continuous delivery services for machine learning applications. While professionally focused on data and analytics, Daniel has a passion for building delightful interfaces to enable the broad consumption of complex mathematical models.
Portfolio
Experience
- Mathematical Finance - 9 years
- React - 6 years
- Python - 6 years
- Data Engineering - 4 years
- Machine Learning Operations (MLOps) - 3 years
- Spark - 3 years
- Scala - 3 years
- Flutter - 2 years
Preferred Environment
Linux, Rust, Flutter, Spark, Python, Scala, Git, Kubernetes, Visual Studio Code (VS Code)
The most amazing...
...mobile app I've developed is a financial option pricing engine which efficiently computes calls and puts when the underlying asset follows a Levy process.
Work Experience
Head of Data Platforms
Regions
- Built the data engineering and machine learning operations team from scratch.
- Developed self-service continuous deployment pipelines to allow data scientists to safely deploy their models. Full provenance from data to code and model objects.
- Successfully operationalized 100% of the models developed by the data science team over the last three years.
- Developed data pipelines to transform raw source-system data into analytics-ready data marts.
Senior Auditor
BB&T
- Validated financial models, including economic capital, stress testing models, and market and option pricing models.
- Performed data testing and provided self-service data extraction tools to auditors as part of the initial audit analytics team.
- Developed full-stack applications for executing continuous testing on key data sources.
Experience
Option Pricing Mobile Application
Efficient Computation of "Loss Distribution Approach" to Operational Risk
Efficient Computation of Portfolio Credit Risk
Fixed-income VaR Calculation
Onkyo Remote Control
It currently has a 4.6 rating out of 63 reviews on Google Play.
Education
Master's Degree in Mathematical Finance
University of North Carolina Charlotte - Charlotte, NC
Skills
Libraries/APIs
React, Node.js, Spark ML, REST APIs
Tools
Git, Apache Airflow
Frameworks
Spark, Flutter, OAuth 2
Languages
Rust, Python, Scala, SQL, C++, Java, Solidity
Paradigms
REST
Platforms
Linux, Kubernetes, Visual Studio Code (VS Code), Google Cloud Platform (GCP), Amazon Web Services (AWS), Android
Other
Mathematical Finance, Data Engineering, Machine Learning Operations (MLOps), GitOps, Monte Carlo Simulations
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