I am a Data Scientist with a background in Electrical Engineering and a Master's in Electronic Systems, an MBA in Project Management. At Shape Digital, I focus on developing predictive maintenance models using spindle data and build Python-based libraries and frameworks to support high-volume data workloads and enterprise software solutions. I have also worked on projects involving anomaly detection in offshore sensor data, corrosion detection using computer vision, and current working developing models for process safety and risk assessment for offshore plants.
My journey into data science began during my Master's, where I published the paper ‘Comparative Study of Photovoltaic Power Forecasting Methods.’ I further deepened my expertise during a research internship at THI - CARISSMA in Germany, contributing to the paper ‘Rapid Estimation of Occupant Crash Behavior.’
In my previous work, I have developed models focused on risk prevention for infrastructure damage in natural gas distribution networks, optimized client prospecting strategies for portfolio management, implemented fraud detection systems in health insurance, and analyzed score behavior and credit risk.
With over 5 years of experience, I specialize in Python, PySpark, SQL, Azure, and Databricks. I have worked on end-to-end model development, from data collection and preprocessing to deployment, maintenance, and ongoing support for clients. I have also collaborated with cross-functional teams, working alongside professionals from various fields and directly engaging with clients to understand their needs and deliver solutions. My curiosity and passion for data science drive me to solve complex business challenges and create strategic impact.
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