About Me

I am more than a data scientist or programmer — I am a builder. Throughout my career, I have consistently identified problems, designed solutions, and delivered working products that create measurable value. My experience spans data science, data engineering, software development, cloud architecture, and artificial intelligence, allowing me to bridge the gap between business needs and technical execution.

I have built analytics platforms, AI-powered applications, clinical data solutions, cloud-based systems, APIs, machine learning models, and reusable software packages. I am equally comfortable discussing strategy with stakeholders, designing scalable data architectures, developing production-ready code, and deploying solutions to the cloud.

What sets me apart is not a specific programming language or technology stack, but my ability to learn quickly, adapt to new domains, and take ownership of complex problems from concept to delivery. Whether working with clinical trial data, real-world evidence, financial systems, legal technology, or generative AI, I focus on creating practical solutions that improve efficiency, generate insights, and solve real business challenges.

At my core, I am an entrepreneur, engineer, and problem solver who enjoys building things that did not exist before. When I see an opportunity for improvement, I do not wait for someone else to solve it — I take the initiative to design, build, and deliver the solution myself.

What I work with

• Languages: Python, R, SQL
• Data & AI: pandas, NumPy, scikit-learn, dbt, LangChain, Claude API
• Cloud: AWS (Glue, S3, Athena, Lambda, Amplify)
• Visualization: matplotlib, seaborn, Plotly, Tableau

Get in touch

Find me on GitHub, LinkedIn, or use the contact form.