About
I'm a detail-oriented Data Scientist with 3+ years of experience applying statistical modeling, machine learning, and data engineering to solve complex problems in finance and analytics. I started out building production software at S&P Global in the financial data space, moved into ML research at Florida State University, and along the way developed a strong foundation in mathematics and a real passion for financial systems and Python. I like sitting at the intersection of math, engineering, and finance, and I'm always chasing problems that are hard enough to be interesting. Looking for exciting opportunities to work and collaborate with bright minds and explore the world of data together.
Outside of work, I enjoy exploring cafés, gaming, photography, and going on nature walks.
If you're embarking on an exciting project or seeking fresh perspectives, don't hesitate to reach out via Mail or Whatsapp. I'm always eager to connect, exchange ideas, and explore new avenues of exploration and growth together.
Check out some of my photography work on VSCO.
About this site
Welcome to my home on the internet. This site functions as a blog/portfolio, a place to share code and thoughts. Opinions of my own.
I learnt how to build this site from the most awesome people in the community:
- Timothy's Next.js and Tailwind CSS template: Template starter where I bootstrapped the project.
- Einar Guðjónsson: Now page, navigation style, animations and much more.
Experience
Data Scientist @ APD
June 2025 – Present- Process and analyze 200K+ records across Medicaid, vendor, and client systems serving 60,000+ individuals — merging data from SQL Server, S3, and internal systems into unified datasets, and leading development of Power BI dashboards and automated reports (Python, SPSS) for executive leadership and agency staff.
- Optimize SQL queries and data pipelines through indexing, partitioning, and caching strategies, reducing report execution time by 83% (60 minutes to under 10 minutes).
- Conduct statistical analysis using SPSS, SAS, and R to uncover billing anomalies, forecast financial trends, and deliver compliance insights, improving audit accuracy and budgeting. Lead ad hoc and recurring data support for cross-functional teams, cutting manual workload by 40% through reusable code pipelines.
AI/ML Researcher @ Florida State University
June 2024 – September 2024- Researched open-source generative AI models and algorithms (GANs, VAEs, RNNs) to explore synthetic data generation for material property prediction and battery optimization applications.
- Implemented and benchmarked NequIP (MIT open-source) for molecular stability prediction across an 11,000+ material dataset, improving prediction consistency by ~15% during initial validation.
- Collaborated with PhD researchers in Chemistry to align data science workflows with experimental research goals, enhancing interdisciplinary research on AI-driven material discovery and energy storage.
Software Developer @ S&P Global
January 2022 – August 2023- Identified a migration opportunity as an intern — auditing S&P's legacy .NET document-processing workflows against open-source alternatives (regex, pdfplumber, Camelot, Tesseract, Textract) — then led a team of 5 through the migration, owning the architecture and rollout of a Python-based extraction platform across multiple business domains, cutting licensing costs 80% and improving extraction speed 30%.
- Built the pipeline layer on Docker/AWS to process 10,000+ financial and automotive documents daily with retry logic, structured logging, and fault-tolerant processing, reducing manual extraction time by over 90%. Combined OCR with CNN-based classification to turn unstructured PDFs and scanned documents into structured data, improving entity recognition accuracy on financial documents.
- Engineered the platform for long-term maintainability with modular, reusable components, CDC-based incremental updates, and 80% test coverage, backed by GitHub Actions CI/CD for reliable releases.
Software Developer Intern @ LG Electronics
May 2021 – August 2021- Built a real-time drowsiness detection system using Python, OpenCV, YOLO, and Raspberry Pi, achieving 90% facial landmark accuracy to improve driver safety in logistics operations.
- Designed a CNN-powered logistics tracking system integrated with REST APIs and PostgreSQL, reducing package sorting time by 25% across the logistics workflow.
- Awarded 3rd place in LG's internal Ideathon competition for the logistics tracking system built during the internship.
Software Developer Intern @ ITC Limited
January 2021 – March 2021- Developed a master data management system using Python (Flask, REST API) and MySQL with multi-role access control across admins, users, and vendors.
- Implemented role-based authentication and approval workflows to improve data security and streamline user operations across business units.
- Automated product tracking and data update processes, reducing manual workload by 30% and enhancing data accuracy across multiple business units.