Aspiring ML Engineer & Data Scientist based in Chicago
Email: [email protected] • LinkedIn

I’m currently completing my Master’s in Artificial Intelligence at the Illinois Institute of Technology, where I’ll graduate in May. My passion lies at the intersection of data science, machine learning, and solving complex real-world problems. I thrive on continuously learning and experimenting with new AI techniques, striving to stay on the cutting edge of what machine learning can do.

• Location: Chicago, IL
• Interests: Machine Learning, Data Visualization, Statistical Analysis, MLOps
• Achievements & Honors:
  • Grainger Innovation Prize Finalist (2024)
  • Hack Midwest Finalist (2023)
  • Member of Upsilon Pi Epsilon (Computing & Information Honors Society), Phi Theta Kappa, and ACM
  • Transfer Leadership Scholar and Dean’s List honoree

During my time at Siemens, I tackled real-world challenges in computer vision and data-driven modeling. In my current role as a Python Developer, I focus on designing and implementing robust ML pipelines. I’m also proficient in Docker and Kubernetes, enabling seamless deployment and scalability for AI applications.

• Summary: Led a team to develop an AI-driven traffic management solution.
• Tech: Python, NumPy, Pandas, Scikit-learn, GANs, Hugging Face Transformers
• Impact: Achieved 95% accuracy in modeling traffic flow and reduced accident rates by 48.2% in simulations.

• Summary: Combined sentiment analysis on 2.7+ million news articles with historical stock data to predict market trends.
• Tech: Python (TensorFlow, Scikit-learn, Pandas), VADER for NLP sentiment
• Impact: Achieved 62.4% average directional accuracy for next-day predictions.

• Summary: Created a lightweight 3D reconstruction model inspired by Apple’s FineRecon.
• Tech: MobileNets, Depthwise Separable Convolutions
• Impact: Reduced model parameters by 15.19% with under 3% loss in quality, enabling real-time processing on resource-constrained devices.

• Summary: Developed a lightweight GAN (inspired by Goodfellow et al.) to generate high-quality synthetic data.
• Tech: Python (TensorFlow/PyTorch)
• Impact: Improved performance speed by 36.7% and achieved an Inception Score of 6.73.

• Summary: Partnered with industry to create an AI-driven drone flight planner.
• Tech: Advanced ML techniques for path prediction and tracking
• Impact: Increased processing speed by 6.3% while maintaining accurate trajectory mapping.

• Summary: Deployed a Retrieval-Augmented Generation (RAG) chatbot for data mining queries.
• Tech: LlamaIndex, LangChain, Docker, AWS (S3, Lambda, API Gateway)
• Impact: Answers queries 9.2% more accurately than ChatGPT and responds in under one second.

• Programming Languages: Python, R, JavaScript, (and more)
• ML Frameworks: TensorFlow, PyTorch
• Data Analysis: Statistical techniques, data visualization, model optimization
• DevOps & Deployment: Docker, Kubernetes, AWS, Git

I believe in leveraging these tools to build scalable, efficient, and impactful AI solutions.

I’m actively seeking Data Scientist or Machine Learning Engineer roles in Chicago. If you’re looking for someone passionate about driving innovation through data and machine learning, let’s chat!

• Email: [email protected]
• LinkedIn: linkedin.com/in/n-d-al
• GitHub: github.com/nick-allison

Feel free to reach out or explore my repositories to see more of my work. I’m always open to collaborations, feedback, and new opportunities!

“Data is the new oil, and I’m here to refine it.” – Nick Allison