Transforming Data Into Insights
Data Scientist & Software Engineer bridging research and technology
About Me
I'm a passionate data scientist and software engineer with expertise in machine learning, statistical modeling, and full-stack development. I bridge the gap between cutting-edge research and practical software solutions.
My academic background in computer science and applied mathematics fuels my ability to tackle complex problems with both theoretical rigor and engineering pragmatism.
Research
Published papers on deep learning architectures and NLP applications in peer-reviewed journals.
Development
Built scalable machine learning pipelines and full-stack applications for enterprise clients.
Education
PhD in Computer Science with focus on machine learning and natural language processing.
Experience
Senior Data Scientist
2020 - PresentTech Solutions Inc.
- Led development of ML models improving customer retention by 32%
- Designed and implemented real-time anomaly detection system
- Mentored junior team members on best practices in ML engineering
Machine Learning Engineer
2017 - 2020InnovateAI
- Developed NLP models for automated document processing
- Optimized model performance leading to 4x inference speed improvement
- Published research on transformer architectures for low-resource languages
Research & Projects
Deep Learning for NLP
Novel architecture for sentiment analysis achieving state-of-the-art results on benchmark datasets.
Analytics Dashboard
Interactive dashboard for real-time business metrics visualization with anomaly detection.
Federated Learning
Privacy-preserving ML framework for healthcare applications using federated learning techniques.
ML Ops Pipeline
Automated machine learning pipeline with CI/CD integration for production model deployment.
Education
PhD in Computer Science
Stanford University
2014 - 2018
Dissertation: "Advances in Deep Learning for Natural Language Understanding"
MS in Applied Mathematics
MIT
2012 - 2014
Research in probabilistic graphical models and optimization algorithms
Publications
Transformer Architectures for Low-Resource Languages
2022Neural Information Processing Systems (NeurIPS)
Proposed a novel transformer variant improving performance on underrepresented languages by 17% compared to baseline models.
Latest Writings
May 15, 2023 • 8 min read
Explainable AI in Modern Data Science
Exploring techniques to make complex machine learning models more interpretable and transparent.
Read More →
April 2, 2023 • 12 min read
The Math Behind Neural Networks
A deep dive into the mathematical foundations powering modern deep learning architectures.
Read More →Get In Touch
Contact Information
researcher@dataalchemy.com
Location
San Francisco, CA
linkedin.com/in/data-scientist