VISION, CONSISTENCY, FOCUS, TENACITY
Brooklyn, NY 11201
Far-sighted, Analytical and Customer-Focused Data Science Professional with demonstrated expertise in delivering research-based, data-driven solutions that move organizational visions forward. Highly competent at Implementing statistical methods to solve specific business problems utilizing code and improving existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters. Experienced at creating data regression models, using predictive data modeling, and analyzing data mining algorithms to deliver insights and implement action-oriented solutions to complex business problems. Unparalleled capacity to link quantitative and qualitative statistics to improvements in operating standards with expert knowledge of mathematical concepts and data management protocols. STRENGTHS SNAPSHOT
Strategic Planning & Tactical Execution
Business Development/Business Intelligence
Data Communications & Quantitative Analysis
Performance Metrics & Insights
Big Data Queries and Interpretation
Project Lifecycle Coordination
Machine Learning Algorithms
Data Mining, Visualization & Management
Data Analysis, Extraction & Manipulation
Research, Reports & Forecasting Systems
Predictive Analysis/Process Improvements
Operational Efficiency/Network Programming
CAREER NARRATIVE & MILESTONES
Union Pacific Railroad Omaha, NE January 2018 – December 2019 Data Scientist
Fueled business development opportunities by designing a model that can predict company’s sales of new products based on historical purchase data from an online shop, achieving a 25% more accurate prediction of performance than in previous years and saving the company an extra $220,000 in the manufacturing cost of goods sold.
Propelled innovation and game-changing technological advances to Identify problematic fuel sensors and executed strategies and models to examine the accuracy of each sensor, and to detect inaccurately in running sensors which saved the company $2,075,000 in unnecessary costs
Utilized technical knowledge of predictive analytics including machine learning and data mining techniques to forecast company sales of new products which yielded a 69% accuracy rate.
Presented data and conclusions to team in order to improve strategies and operations.
Proposed solutions to improve system efficiencies and reduce total expenses.
Modernized capabilities within organization involving the classification of documents according to their labels by introducing Machine Learning models that take numerical values as input, using logistic regression, Naive Bayes, SVM, XGboost to fitting models, thereby improving and streamlining operational efficiency. EDUCATION
Master of Science in Mathematics(Concentration: Data Science) – University of Nebraska, Omaha, NE Bachelors of Arts in Psychology / Bachelor of Arts in Mathematics – University of Buffalo, New York, NY HONORS & AWARDS
Pi Mu Epsilon American Mathematical Society
R, SQL, Python, ADV Machine Learning Methods, Data Visualization, Data Cleaning, Tableau, Spark, Beam PROGRESSIVE-LEVEL DATA SCIENTIST
LEVERAGING EXTENSIVE SUPERVISORY EXPERIENCE TO LEAD TEAMS IN ACHIEVING/EXCEEDING BIG DATA SET TARGETS, BOASTING AN IMPRESSIVE RECORD OF SIGNIFICANTLY IMPROVING OPERATIONS