Paul Victor

Background

About Paul Victor

I am an experienced data scientist/statistician who enjoys using my strengths of data science algorithms and statistical analysis to merge and sift through large non-structured and structured datasets to draw business insight and pattern discovery. As well as a strong analytical background I have strong presentation skills that allow me to translate advanced topics that technical engineers and management can benefit from. Some methods and concepts I have applied in industrial applications and academic research are Deep Convolutional Neural Networks, Linear Regression, Regularization Regression Models, Random Forest, XGBoost, KMeans Clustering, PCA, and more. With a deep understanding of these algorithms I am able to identify which is best used for each unique business situation and which will allow for a better result. I enjoy learning new programs/coding languages which is beneficial with our always changing technological world. Most recently this ability has allowed me to enhance my company’s capabilities in visual business programs. I also utilize my skills with R, Python, SAS, and SQL to streamline and optimize business acumen decisions. On an everyday basis, I am consulting with cross functional teams and leading projects that will bring the business closer in achieving its short and long term goals. I pride myself in hard work, adaptability, and approaching abstract problems in a way others do not. This allows me to bring new ideas to the team and challenges others to think on a more critical level.