Cameron Laedtke

About Cameron Laedtke

As a data scientist with a background in physics, I excel in applying machine learningand natural language processing techniques to solve data challenges acrossvarious industries. My proficiency in Python, SQL, and multiple data sciencelibraries enables me to develop and optimize data-driven models that enhancedecision-making and operational efficiencies. I have a proven track record inpredictive analytics, data visualization, and automation.Portfolio: https://camlaedtke.github.io/My work experience includes* Leveraging large language models for large-scale text analysis, using tools such as OpenAI API and Scikit-Learn.* Developing supervised and unsupervised deep learning models for image-based applications, using tools such as TensorFlow and Scikit-learn.* Building and deploying machine learning algorithms on sensor-based streaming data, using model-interrogation techniques such as SHAP analysis* Developing web applications for data visualization and machine learning, using the Dash Python library* Data wrangling and visualization, using Python libraries including Pandas, Numpy, Matplotlib, Plotly, and Bokeh* Relational databases, with experience running queries using PostgreSQL in PgAdmin* Implementation of CI/CD pipelines using Gitlab* Presentation of technical subjects to internal stakeholders in varying levels of technical detail

Experience

1. Solutions Consultant

   Deloitte

   Jul 2024 — Present · Denver, CO, US

   Deloitte Risk and Financial Advisory Group, within Government and Public Services

Education

• University of Minnesota

  Bachelor’s Degree, Physics

  2016

• IES Abroad

  Political Science and Government

Skills

• Microsoft Office
• Sql
• Mathematica
• Java
• Matlab
• Python
• Amazon S3
• Swift
• Data Visualization
• R