Benjamin P. CarteR
ML Engineer, Data Scientist
(513) 418 - 1521
Bowling Green State University, Bowling Green OH
· Applied Statistics & Operations Research, M.Sc. August 2016
· Economics, M.A. December 2014
The Ohio State University, Columbus OH
· Electrical and Computer Engineering, B.Sc. May 2007
Senior data scientist with over 13 years of IT experience, and 8 years of Data Science experience. I’ve been developing Python solutions for over 9 years with experience with R, C, C++, Java, and SQL.
-Experience in the application of Naïve Bayes, Linear and Logistic Regression Analysis, Neural Networks, Time-Series analysis and Random Forest machine learning techniques.
-Experience in statistical models on, big data sets using cloud/cluster computing assets with AWS and Azure.
-Strong ability to devise and propose creative and innovative ways to look at problems by using business acumen, data models, statistical analysis, and a practical and direct understanding of the subject matter.
-Highly capable of discovering patterns in data using both algorithms, visual representation, and intuition. Ability to use experimental and iterative approaches to validate findings.
-Advanced statistical and predictive modeling techniques to build, maintain, and improve on real-time decision systems. Recommendations are strengthened with precise analysis, a real-world intuition, and an adogmatic approach to modeling techniques.
-In-depth knowledge of statistical procedures that are applied in both Supervised and Unsupervised machine learning problems.
-Ability to perform exploratory analysis on varying types of data and datasets, allowing for a full knowledge of the subject matter, a nuanced understanding of the variables in question, and a technically sound insight into the required modeling approach.
-Strong background of working with advanced analytical teams to design, build, validate and refresh data models.
-Excellent communication skills (verbal and written) to communicate with clients/stakeholders and team members.
-Highly perceptive with other people, allowing for a strong ability to facilitate a dynamic and constructive team environment.
-Ability to quickly gain a keen understanding of niche subject matter domains via research and communication with all parties involved. Ability to design and implement effective novel solutions to be used by other subject matter experts.
Analytic Development: Python, R-Programing, SQL, Excel
Python Packages: Numpy, Pandas, scikit-learn, TensorFlow, SciPy, Matplotlib, Seaborn
IDE: Jupyter, Spyder, RStudio, Google Colab, MySQL
Version Control: GitHub
Machine Learning: Natural Language Processing & Understanding, Machine Learning algorithms including text recognition, image classification, and forecasting.
Data Query: Azure, Google, SQL, data warehouse, data lake and various SQL databases and data warehouses.
Deep Learning: Machine Perception, Data Mining, Machine Learning algorithms, Neural Networks, TensorFlow, Keras. PyTorch
Artificial Intelligence: Text Understanding, Classification, Pattern Recognition, Recommendation Systems, Targeting Systems, Ranking Systems, and Time Series.
Analysis Methods: Advanced Data Modeling, Statistical, Exploratory, Bayesian Analysis, Inference, Regression Analysis, Multivariate analysis, Sampling methods, Forecasting, Segmentation, Clustering, Sentiment Analysis, Predictive Analytics, Decision Analytics, Design and Analysis of Experiments, Factorial Design and Response Surface Methodologies, Optimization, and State-Space Analysis.
Analysis Techniques: Classification and Regression Trees (CART), Random Forest, Gradient Boosting Machine (GBM), TensorFlow, PCA, RNN including LSTM, Linear and Logistic Regression, Naïve Bayes, Simplex, Markov Models, and Jackson Networks.
Data Modeling: Bayesian Analysis, Statistical Inference, Predictive Modeling, Stochastic Modeling, Linear Modeling, Behavioral Modeling, Probabilistic Modeling, Time-Series Analysis
Applied Data Science: Natural Language Processing, Machine Learning, Text Recognition, Image Classification, Social Analytics, Predictive Maintenance
Soft Skills: Excellent communication and presentation skills; ability to work well with stakeholders to discern needs accurately and articulate issues clearly; leadership; mentoring; coaching.
Cincinnati, OH (3/17- present)
·Managed all data analysis, including customer, logistical, and market information.
·Used R to clean data, formulate returning customer information not available within the local database, and interpret the analysis for strategic and managerial decisions.
·Led a team of diverse members to identify inconsistencies in the manufacturing process and develop a process of analysis and reporting of possible changes through the future.
·Used both linear regression and artificial neural networks (ANN) to predict product lifetime, in order to accurately report expiration dates. Used results to analyze the production of the product in order to maximize the product’s lifetime.
·Created and maintained new reports and metrics to master awareness of the market and advance customer loyalty.
·Aided in pricing of new product lines and marketing strategies based on customer data analysis. Used time series analysis (ARIMA and LSTM neural networks) to predict weekly, monthly and annual sales of specific products and the entire store.
·Tracked Twitter text regarding product line and performed sentiment analysis using text cleaning techniques, transfer learning, and recurrent neural networks, specifically LSTMs.
Contract Data Analyst
Denver, CO (10/16-12/16)
· Built various production and custom models for both nonprofits and businesses in a wide variety of industries.
· Built and integrated logistic and linear regression models, balancing various internal requirements of covariance and variable criteria.
· Used decision trees and random forests to grade the validity of the variables used in the regression models. Implemented additional tools such as bagging and boosting (AdaBoost, XGBoost) in order to strengthen these models.
· Supported the statistics department in larger, less routine projects.
Bowling Green State Univ.
Research Associate Econometrics
Bowling Green, OH (9/12-9/16)
· Used data and analytics while working at both the Center for Regional Development and Center for Institutional Research.
· Performed analysis on both local economic data and internal university data regarding retention and performance.
· Used K – Nearest Neighbor classifiers to predict the performance of local businesses with respect to geographies, industry, and participation in university business programs.
· Used Artificial Neural Networks to predict retention rates and recidivism of students at the university.
· Graded and proctored examinations for multiple Economics and ASOR classes.
Columbus, OH (9/11-8/12)
· Aided in a time-critical line improvement team.
· Collected, analyzed, and presented operational data daily.
· Utilized logistic regression in a survival analysis of a product line. Using this analysis, estimated time to failure while considering several human and environmental factors.
· Worked for and with the network engineers, line engineers, human resources representatives, and chief project engineer.
· Developed skills in project management at varying levels.
Honda of America Mfg., Inc.
Marysville, OH (9/10-8/11)
· Operated within the electrical component quality assurance team.
· Performed data collection, formulation, and presentation of findings.
· Executed tests in various extreme environments.
· Implemented a linear regression model and analysis to estimate the declining efficacy of spark plugs in sub-zero environments. This model feature various environmental and manufacturing variables allowing it to be generalized across several product lines.
Cisco Systems, Inc.
Iselin, NJ (7/07-12/09)
· Worked within a devoted sales team for a multinational service provider, targeting the core network.
· Presented core routing solutions and new product lines to sales team and the customer's key planning engineers.
· Led initiative to formally enter, track, and update the sales team and customer with the customer's technical requests and requirements.
· Introduced to corporate environment, long lifecycle strategic sales, and world class testing facilities, engineers, and processes.
· Contributed and led sales strategy exercises.
· Developed business acumen, networking knowledge, and sales experience.