Simulation Engineer | M.Sc. Computational Methods in Engineering | M.Sc. Chemical and Energy Engineering | B.Eng. Mechanical Engineering. Data Scientist with over 3 years of experience in Python, machine learning, and statistical analysis, turning complex datasets into actionable insights. Proficient in Python, SQL, and data visualization tools, with hands-on experience building and deploying machine learning models using industry-standard frameworks. Skilled in simulation and modeling, with a strong interest in optimizing both conventional and renewable power systems. Passionate about applying data science to drive innovation across industries—especially in the sustainable energy sector. At Fraunhofer ISE, I developed HelioSliders, a data-driven optimization algorithm that increased solar tower optical efficiency by 3 percentage points over the benchmark, boosting annual energy yield by an estimated 1.2 GWh for a 6 MW CSP installation, showcasing the potential of intelligent algorithms in renewable energy performance.