As a data analyst with a background in physics, I excel in applying machine learning
and natural language processing techniques to solve data challenges across
various industries. My proficiency in Python, SQL, and multiple data science
libraries enables me to develop and optimize data-driven models that enhance
decision-making and operational efficiencies. I have a proven track record in
predictive 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