Daniel Stahl, Developer in Birmingham, AL, United States
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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.



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

2016 - PRESENT
  • 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.
Technologies: Spark, Spark ML, GitOps, Data Engineering, Kubernetes, Machine Learning Operations (MLOps), Apache Airflow

Senior Auditor

2014 - 2016
  • 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.
Technologies: React, Git, Node.js, SQL

Option Pricing Mobile Application

A Flutter app with a financial pricing engine back end written in Rust. It leverages the technique in Fang-Oosterlee's 2008 paper for efficiently inverting the characteristic function of a Levy process.

Efficient Computation of "Loss Distribution Approach" to Operational Risk

Using the results from my peer-reviewed paper on operational risk, I efficiently computed an extended "loss distribution approach" for computing the tail risk from operational risk.

Efficient Computation of Portfolio Credit Risk

Using the results from my peer-reviewed paper, this project computes the loan-level risk contributions efficiently for even large portfolios. The model includes the ability to incorporate liquidity risk in the calculation of credit economic capital.

Fixed-income VaR Calculation

Compute the value at risk (VaR) using Monte Carlo techniques for common fixed-income options, including caps and floors, swaptions, Eurodollar futures, and bond puts and calls.

Onkyo Remote Control

Created a plugin for the "Yatse" mobile application that allows remote control of Onkyo A/V receivers. Control volume and add custom commands.

It currently has a 4.6 rating out of 63 reviews on Google Play.
2011 - 2013

Master's Degree in Mathematical Finance

University of North Carolina Charlotte - Charlotte, NC


React, Node.js, Spark ML, REST APIs


Git, Apache Airflow


Spark, Flutter, OAuth 2


Rust, Python, Scala, SQL, C++, Java, Solidity




Linux, Kubernetes, Visual Studio Code (VS Code), Google Cloud Platform (GCP), Amazon Web Services (AWS), Android


Mathematical Finance, Data Engineering, Machine Learning Operations (MLOps), GitOps, Monte Carlo Simulations

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