I’m a Quantitative Researhcer and Economist with a passion for high-performance computing, scientific research, and data-driven solutions. Over the past ten years, I’ve honed my skills in Julia, Python, MATLAB, and C++ (begginner)—developing efficient, scalable code that tackles complex computational challenges.

My goal is to leverage my expertise in time-series econometrics, numerical methods, algorithm optimization, and data analysis—grounded in deep domain knowledge of economics, macroeconomics, finance and real estate markets—to drive impactful projects that require robust, high-performance solutions. I enjoy collaborating with cross-functional teams and leveraging open-source technologies to develop scalable, data-driven solutions that drive business impact, enhance decision-making, and optimize complex systems.

🔗 Visit my website to check out my academic research and open-source projects: daveleather.com.

• High-Performance Computing (HPC): Experience building and optimizing applications for large-scale computational environments.
• Data Analytics & Scientific Computing: Skilled in data wrangling, statistical modeling, and visualization across varied research domains.
• Algorithm Optimization: Proficient in performance profiling, refactoring, and parallel computing to reduce execution time.
• Cross-Language Collaboration: Comfortable working with diverse languages (Julia, Python, C++, MATLAB) and workflows.
• Open-Source Contributions: Passionate about sharing knowledge and best practices through GitHub and community forums.

I look forward to connecting with you and discussing how we can work together to build something impactful!