Hi there! I’m Emily F. Gorcenski, and this is my personal website. Before going further, please note that the opinions share on this site belong only to me and I do not speak for my employer or any other organization unless stated otherwise. I am a data scientist by profession, a mathematician and engineer by training, and an activist by passion. On this page, you’ll find a brief CV, bio, and other information that you might care about or need.

Short Autobiography

I am a data scientist and engineer by training and a social justice activist by passion. Occasionally, I write about politics, software, and politics-in-software. I am also a regular conference speaker.

I studied Aeronautical Engineering and Mathematics at Rensselaer Polytechnic Institute in Troy, NY. My degree is in Mathematics, and my focus is on Numerical Analysis and Uncertainty Quantification. My undergraduate research fellowship was done at the Princeton Plasma Physics Laboratory, and I spent the first part of my career in research and development before shifting to data science and engineering. I have worked in a wide range of technical fields, from aerospace control systems, signal processing, video game development, occupational therapy for rehabilitation, and more. Some of my work is summarized in my CV below. Presently, I work as a data science and data engineering consultant for Thoughtworks Germany, where I help clients build high-quality data-driven, intelligent software applications efficiently.

In addition to my regular professional work, I also sit on the advisory boards of the Prosecution Project at Miami University in Ohio (Dr. Michael Loadenthal), and on the Youth Equity and Sexuality Laboratory at Suffolk University (Dr. Mimi Arbeit), two research labs studying political violence. My experience in contemporary right-wing violence is driven in large part by my personal experiences as a survivor of neo-Nazi terrorism in my home city of Charlottesville, Virginia, when terrorists came to the Unite the Right neo-Nazi hate rally intent on doing violence. As part of my efforts to understand this violence, I created First Vigil (offline but returning soon), a database of criminal cases involving hate crimes, right-wing anti-government militancy, and white supremacist violence. For that work, I’ve been given accolades; among them, I was named as one of 2018’s most influential feminists by Bitch Magazine.

My research into the far-right has been part of several stories. My research, footage, and experiences were part of Documenting Hate, a documentary by PBS Frontline and ProPublica that won an Emmy in 2019. The Peabody and Emmy Award-winning documentary, Charlottesville: Race and Terror focused on neo-Nazi Christopher Cantwell, who days later became internationally-known as “The Crying Nazi” after learning I had sworn a felony warrant against him. I was (briefly) depicted as a fictionalized character in American Horror Story: Cult, and I have been the focus of several news stories, including a front-page feature in the Washington Post, a profile in Motherboard, a profile in The Guardian, and a profile in Die Tageszeitung (German).

From time-to-time, I turn my research and experience into published analysis and opinion, some of which are linked in the Publications section of my CV below. I am available as a guest on TV appearances and have appeared on programs from TODAY to Al Jazeera’s The Stream. Please email me at the above email address if you would like me to appear on your segment. I am also available for conference talks. For previous talks, please see the Conferences section below. I am currently offering talks in the following topic areas:

  • continuous delivery for data-driven software;
  • data mesh;
  • data reliability engineering;
  • the social role of technology and technologists in contemporary society;
  • joyful intersections of math and technology.

Thanks for reading!

Curriculum Vitae


Head of Data: ThoughtWorks Deutschland GmbH, Berlin, Germany

August 2018 — Present

ThoughtWorks is a global technology consultancy that helps its clients excel at software development. With offices in 17 countries and over 11,000 employees, Thoughtworks is a recognized leader in software engineering, Agile, and other technology best practices.

I am a Principal Consultant, Data Scientist, and serve as Head of Data and AI for Thoughtworks Germany and Thoughtworks Europe. In my role, I advise clients in a variety of technology development efforts in the data science space. These efforts can include: consulting on data mesh transformations, designing effective data platforms to empower faster data analytics and data science, data research and exploration, and implementing agile workflows and continuous delivery for machine learning applications. My unique experience in technology transition means I am well-suited for both advisory and delivery roles in the data science space. Some of my accomplishments with ThoughtWorks include:

  • Designing and building a location analytics platform for land use analysis;
  • Designing workshops for teaching continuous delivery and agile development methodologies in a data science space;
  • Training project and product managers on effective ways to utilize data and data scientists on cross-functional teams.
Senior Data Scientist: Simple, Portland, USA

September 2016 — May 2018

Simple Financial Technical Corporation is a personal finance company acting as a technology-first organization. The core product is a consumer checking account with an app-first design. The company offered web, iOS, Android, and mobile-web apps to allow customers to manage finances, interact with support, and plan budgets. The company operated no physical branches.

I worked as Senior Data Scientist, where I analyzed customer behavior, including app usage spending/saving behavior, customer satisfaction, and fraud detection and mitigation. Additionally, I served as mentor for six other data scientists with varying levels of experience and skills. Key accomplishments include:

  • Building a generalized genetic algorithm framework for optimizing risk models;
  • Implementing and maintaining a knowledge repository for insight documentation;
  • Developing and implementing an improved fraud-detection model with rapid deployment needs;
  • Designing experiments to quantify customer behavior and assess feature feasibility.
Research Engineer: Barron Associates, Inc., Charlottesville, USA

April 2008 — May 2016

Barron Associates, Inc. is a small research engineering firm specializing in real-time control systems, simulation, and mathematical modeling in the aerospace, automotive, and biotechnology fields. Predominantly working in technology transition—the complex space between core research and technology implementation—Barron Associates helped move technologies and methodologies from university laboratories to production environments within industry and government.

I served Barron Associates as a Research Engineer. Using my background in computational mathematics, I worked on interdisciplinary teams with world-class domain experts to help demonstrate and prove complex algorithms and ideas in real-world environments. In addition, I wrote winning grant proposals for new work, led multi-center teams, and presented the company’s work and vision before industry and academic professionals. A sample of my projects is presented below.

Intelligent Prognostics for Vehicle Maintenance Planning

Objective: Using engine, powertrain, and vehicle telemetry, dynamically detect degraded performance to schedule preventative maintenance and allow for greater variability in maintenance schedules.

Approach: Using MATLAB and Simulink, developed a high-fidelity model of engine and vehicle dynamics. Applied modeling approach to large-scale real-world datasets to identify performance and detect failures. Used inverse methods to correct for sensor bias and noise. Applied Kalman filtering techniques for fault detection.

Neural Networks for Low-Resolution Image Classification

Objective: Develop a method for identifying humans in variable sea-state conditions using low-resolution radar images.

Approach: With the requirements of running on real-time embedded hardware, developed a feature extraction pipeline based on Hough Transformations to extract image data. Built a multiclass classification algorithm using polynomial neural networks. Trained and validated data in a real-world environment using a functional radar platform.

Wearable Health Tracker for Lower-Limb Amputees

Objective: Develop a wearable IoT health monitor for lower-Limb combat amputees capable of assessing physical health in people with complex medical needs.

Approach: Designed algorithms for a photoplethysmography-based health monitor capable of being embedded within gel prosthetics linings. Ensured algorithms would be functional in atypical conditions e.g. tissue ossification, where commercial health trackers generally fail.

Image Analysis for Automated Corrosion Mapping

Objective: Develop software capable of identifying corrosion pits in laser profilometry scans of nickel-based superalloys corroded at high temperature with sulfur-based salts.

Approach: Used regularization methods to detect pits while preserving surface geometries where convolutional methods would typically fail. Built algorithms for automating volumetric measurement and classifying inclusions to detect conditions that would lead to adverse stress concentrations. Designed software package to output results to commercially-available failure prediction tools.


  • Programming: Python, SQL, C#, MATLAB, FORTRAN, C/C++, Java
  • Python-specific Competencies: Python 3.x, jupyter, pandas, numpy/scipy, keras
  • Frameworks and Technologies: Terraform, neo4j, Postgres, Docker, Jupyterhub, GoCD, CircleCI, Jenkins
  • Cloud Competencies: Azure (AKS, Storage), AWS (Elastic Beanstalk, Route53, S3, Redshift, Lambda), Google Cloud (Firebase, Cloud Storage, Load Balancer, Kubernetes Engine, Compute Engine, Cloud Functions), Databricks, Jupyterhub
  • Tools: Visual Studio .NET/VSCode, Anaconda, git, Jira, Trac, Trello, Chartio, Tableau, Grafana, Scalyr, Lightstep


  • BS Mathematics (applied and computational), 2007, Rensselaer Polytechnic Institute, Troy, NY
  • Post-graduate work (Mathematics), 2011-2014 University of Virginia (non-matriculated), Charlottesville, VA



  • English:
    • Native Fluency (American)
  • German:
    • Conversational (CEFR B2)
    • B2 Zertifikat (Goethe Institut), June 2022
  • Spanish:
    • Lapsed Learner (~CEFR A2)

Published Writing

Selected Technical Talks

(forthcoming events in italics)

  • Big Data Europe, “Four years of Data Mesh in Practice: What works, what doesn’t, and what’s left to learn”, Vilnius, Latvia, November 2023
  • Better Ways, Athens, Greece, September 2023
  • Women in Data & AI, “From Data to Decision”, Berlin, Germany, June 2023
  • SLOConf 2023, “A “moving SLO” for machine learning”, Online, May 2023
  • SLOConf 2022, “A Better SLO for Data-intensive Systems,” May 2022, Online
  • Big Data EU 2021, “Using Service Level Objective Theory to Design Great Data Products,” September 2021, Online
  • Percona Live Online, “SRE for Good: Engineering Intersections between Operations and Social Activism” (keynote), with Liz Fong-Jones (Google), October 2020, Online
  • DeliveryConf, “Continuous Delivery for Machine Learning: Patterns and Pains,” January 2020, Seattle [video]
  • XConf EU 2019, “When Data Meets Device: Looking forward to a data-driven physical world,” July 2019, Manchester & Barcelona
  • SRECon EMEA 2018, “SRE for Good: Engineering Intersections between Operations and Social Activism” (keynote), with Liz Fong-Jones (Google), August 2018, Düsseldorf
  • Mozfest 2017, “Debunking Fake News and Fake Science” (keynote), with Sarah Jeong (New York Times), October 2017, London [video]
  • PyData Berlin 2017, “Polynomial Chaos, a Technique for Modeling Uncertainty,” July 2017, Berlin [video]
  • JSConfEU 2017, “The Ethics of the Internet of Things,” May 2017, Berlin [video]


(forthcoming events in italics)

Posted: 12.12.2018

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Updated: 07.08.2023

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