Physicist with a strong background in statistics , data analysis , and machine learning . Experienced in leveraging statistical methods and mathematical modeling to extract meaningful insights from complex datasets . Skilled in data processing , analysis , and visualization , with a focus on utilizing machine learning techniques to solve real-world problems . Proven ability to work effectively in multidisciplinary teams , contributing to projects
Creating interactive dashboards for real-time insights and automating reporting to streamline processes. Evaluating product performance, managing product lifecycles, and optimizing pricing strategies. Identifying growth opportunities through competitor benchmarking and market trend analysis. Managing key KPIs including inventory turnover, profit margins, customer retention rate, order cycle time, marketing ROI, and sales conversion rate.
Major achievementLeveraging data to drive efficiency, boost sales, and optimize inventory. Utilizing tools like Azure, Siigo, and Power BI for demand forecasting, supplier performance, and process improvement. Analyzing customer segments and purchasing behavior to tailor marketing strategies and identify upselling opportunities.
Analyzing structural energy with Python libraries such as Pandas, NumPy, Seaborn, and Matplotlib. Using software like Grace and PyProcar for electronic and phononic structure analysis. Creating reports using LaTeX. Consolidating bibliographic databases and preparing research projects for internal calls.
Major achievementPost-processing data with VASPkit and Phonopy for electronic and phononic structure analysis. Developing and optimizing computer codes in Python for simulations on supercomputers. Presenting research findings at scientific conferences and contributing to research dissemination.