Michaël Spierer

• Rotating through teams every six months, currently contributing to the Data Analytics team.
• Collaborated with cross-functional teams to identify key performance indicators and develop visually engaging dashboards in Tableau Desktop.
• Integrated multiple sources of disparate data into cohesive datasets using ETL processes, improving overall analytic capabilities.
• Reduced operating costs by automating manual data processes using scripting languages such as Python.
• Enhanced application performance by optimizing Java code and implementing efficient algorithms.

• Thesis Title: Managing IT Incidents with ML and IR Tools: a Case Study with Jira Software
• Designed solutions to enhance users productivity in management of new IT incidents.

Data Handling, Machine Learning, Information Retrieval, Document Embedding, Data Visualization, Data Analysis

Semester Project: Machine Learning to Differentiate Between Signal and Noise in Flow Cytometry.

• Developed innovative machine learning solutions for complex data sets, resulting in improved prediction capabilities.
• Integrated machine learning and predictive analytics into tasks.

Data Handling, Data Analysis, Numpy, Pandas, SKlearn, FlowGrid

• Fine-tuned a deep learning-based object detector.

Machine Learning, Deep Learning, Computer Vision, Python

• Gained valuable experience working within a cybersecurity startup, applying learned concepts directly into relevant work situations.
• Developed a software to automatically regulate Windows security parameters according to Microsoft security policy settings recommendation.

Cybersecurity, Vulnerability Detection, Risk Modeling, Fullstack Development