I transform complex scientific challenges into actionable insights using advanced computational methods, automation, and data analysis. 2+ years developing high-throughput materials discovery workflows and managing large datasets. BSc in Biological and Pharmaceutcial Chemistry, with undergraduate research experience in RNA-based organic synthesis.
Proven skills in data science, automation, and computational modeling with immediate industry applications
Teaching and Academic Research
Real-world applications of computational methods delivering measurable business value
Developed automated screening method for catalyst optimization, processing 700+ material configurations with minimal manual intervention.
Built computational models predicting experimentally relevent materials, enabling data-driven design decisions before expensive synthesis.
Collaborated with experimental teams to validate results using computational methods (DFT), delivering a peer-reviewed publication in a high-impact journal (ACS).
Multi-step organic synthesis of modified RNA monomers to support the RNA world hypothesis.
Peer-reviewed research demonstrating proven ability to deliver high-impact technical solutions
Latest highlights and milestones
I'm seeking opportunities where I can apply my analytical thinking, problem-solving experience, and laboratory skills to contribute to meaningful work. Open to roles in R&D, materials discovery, phramaceuticals, data science/analytics, technical consulting, and related fields.
Target Roles: