Ernie E. Fontes, Data Scientist, Mathematician
| Columbus, US
SUMMARY
Seasoned data scientist and machine learning expert with a PhD in mathematics, driven by a passion for tackling complex challenges and continuous learning. Proven track record of architecting cutting-edge AI applications that solve complex problems at scale, including building a cutting-edge 0-1 fraud detection solution. Expertise in feature engineering, model evaluation, and anomaly detection. Adept in translating business challenges into data-driven solutions, with experience in financial services and startup environments. Adept at cross-functional collaboration and technical presentations. Seeking a role that fosters intellectual growth and leverages state-of-the-art techniques to drive significant business value and societal impact.
EDUCATION
The University of Texas at Austin 2010 — 2017
PhD - Mathematics
The University of Texas at Austin 2010 — 2012
MA - Mathematics
Harvard University 2006 — 2010
BA, cum laude in field - Mathematics
SKILLS
Data Science (Advanced): machine learning, deep learning, fraud detection, classification, regression, supervised learning, multi-class classification, clustering, topological data analysis, data visualization, experimentation, A/B testing, causal inference, hypothesis testing, optimization, anomaly detection, gradient boosted trees, feature engineering, feature selection, model evaluation, MLOPs
Analytics and Communication (Advanced): product analytics, metric definition and evaluation, technical presentation, cross-functional collaboration, data storytelling
Python (Advanced): pandas, NumPy, SciPy, scikit-learn, XGBoost, TensorFlow, Keras, PyTorch, matplotlib, seaborn, Jupyter notebook
Data Engineering (Advanced): SQL, dbt, Snowflake, Prefect, Airbyte, ELT/ETL, data pipelines
Mathematics (Master): algebraic topology, homotopy theory, homotopical algebra, category theory, topology, mathematical problem solving, proof writing, communication of mathematics, graduate mathematics, undergraduate mathematics
Other Skills: git (moderate), AWS (moderate), Linux (moderate), JIRA and Agile methodologies (moderate), Confluence (moderate)
EXPERIENCE
Guardinex | Head of Data Science 2020-09-01 — Present
http://guardinex.com

Guardinex is a start-up solving application fraud in financial services utilizing dark web breach data.

  • Spearheaded all data science, machine learning, and data engineering activities as employee one
  • Pioneered 0-1 product development by architecting and implementing prototypes for all models from scratch, successfully transitioning them from concept to production
  • Instrumental in securing Series A funding (2021)
  • Developed cutting-edge third-party fraud model achieving 0.95 AUC on outstanding credit card fraud cases
  • Innovated first-party fraud model reducing fraud declines by 60% with no additional risk, enabling customer to fund 20% more loans
  • Created novel deposit fraud model capable of detecting 75% of deposit fraud during account creation
  • Executed 35+ B2B customer retrospective proof-of-concepts to support sales: managed 1MM+-row studies, conducted detailed analyses, and crafted compelling business cases
  • Collaborated with product managers to define and track value-driven key performance indicators (KPIs) for sales POCs, aligning data-driven insights with customer needs and product valuation strategy
  • Designed and implemented modern data stack with 120+ data models in dbt on Snowflake, orchestrating ELT with Airbyte and Prefect
  • Recruited and mentored a team of 2 data scientists, fostering a culture of innovation and excellence
  • Architected MLOPs system for seamless deployment, monitoring, and testing of models
The Ohio State University | Postdoctoral Fellow (Ross Assistant Professor) 2017-08-01 — 2020-08-31
https://math.osu.edu/

Conducted research and taught in the mathematics department.

  • Conducted groundbreaking research in homotopy theory, algebraic K-theory, and category theory; authored and submitted two papers
  • Delivered numerous invited talks at prestigious conferences and seminars, enhancing the university's academic reputation
  • Instructed undergraduate and graduate mathematics classes, educating over 600 students cumulatively
  • Established and facilitated a weekly seminar to mentor graduate students in advanced research techniques; executed two successful large-scale conferences showcasing organizational skills
The University of Texas at Austin | Graduate Student Researcher and Teaching Assistant 2010-09-01 — 2017-05-31
https://www.ma.utexas.edu/

Student of Andrew Blumberg; conducted research and served as a teaching assistant in the mathematics department.

  • Conducted innovative research in homotopy theory, presenting findings at multiple conferences and seminars
  • Spearheaded organization of graduate-level seminars and the 2014 Graduate Student Topology and Geometry Conference (GSTGC), fostering academic collaboration and knowledge exchange
  • Excelled as a calculus teaching assistant, earning department teaching award and advancing to oversee all undergraduate course assistants
PROJECTS
Social Media Manager Assistant

AI assistant for generating, managing, and scheduling social media posts across various profiles. LLM interface with prompt engineering, RAG architecture, and Chroma vector database integration.

LANGUAGES
English (Native speaker)
INTERESTS
Baking [ sourdough , pizza ] , Exercise [ climbing , bouldering , yoga , running ]