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Hands-on data science practitioner, driven by the challenge of finding and manipulating data to help build better products and make smarter business decisions. Excels navigating large data sets to support predictive modeling, measurement, advanced analytics, machine learning, and visualization. EDUCATION & CERTIFICATIONSTHE PENNSYLVANIA STATE UNIVERSITY, COLLEGE OF INFORMATION SCIENCE & TECHNOLOGYBachelor of Science (BS) in Data Science (December 2021)• Elected as Lambda Chi Alpha Risk Management Chair (2019)Certifications: MS Excel MOS Specialist Certification; Microsoft MTA Database FundamentalsEXPERIENCETHE PENNSYLVANIA STATE UNIVERSITY, COLLEGE OF INFORMATION SCIENCE & TECHNOLOGYStudent: Data Science (2017 to 2021)Researched emerging trends within the data science field, including natural language processing, image classification, and feature engineering. Applied visual analytic methods and techniques to help support human analytical reasoning with data through Python and d3 in JavaScript. Implemented modern programming models and related software stacks for performing scalable data analytics and discovery tasks over massive and high dimensional datasets using Scala and Spark. Utilized Hadoop Distributed File System (HDFS) to handle large data sets running on commodity hardware.• Created and applied CountVectorizer to convert text to numerical data to be used by a medical practice to categorize content by area of specialty. Created a lemmatization function to group together inflected word forms for analysis as a single item. Utilized the chi2 function from the sklearn Python module for statistical hypothesis testing• Developed a mechanism to classify eye movement (looking right, left, straight, or closed) by splitting data into training and validation folders and using torch.optim.SGD to assure that all parameters were being optimized. Decayed the learning rate by 0.1 after each epoch using lr_schedulur.StepLR. Used the transfer learning model vgg16 for visualization• Achieved proficiency in Python, R, and Java; with hands-on experience using the R Tidyverse, and Python libraries (Pandas, NumPy, ggplot, PyTorch, Scikit-learn). Gained skills in SQL, MongoDB, and Cypher to query and create large datasetsAssisted in database build for the Learning Resources Instructional Design team to track faculty Courses New to Online (CNO) review process, Online Learning (OL) training, and Quality Matters (QM) course reviews.• Migrated database from Excel into Access and introduced a query function to replace manual searches
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Data AnalystExpanaPhiladelphia, Pa, Us
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Junior AnalystExpana Oct 2024 - Present
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Data AnalystCap Index Apr 2022 - Apr 2024Collaborated within a team to efficiently allocate security resources, manage exposure, and optimize losses. Spearheaded the processing and analysis of crime risk assessment-related data, encompassing incidents, loss, demographics, persons of interest (POI), among other variables.Evaluated data suitability and accuracy, pioneering the development of tools for automated data collection. Undertook data cleansing and processing of extensive datasets, alongside the design and management of… Show more Collaborated within a team to efficiently allocate security resources, manage exposure, and optimize losses. Spearheaded the processing and analysis of crime risk assessment-related data, encompassing incidents, loss, demographics, persons of interest (POI), among other variables.Evaluated data suitability and accuracy, pioneering the development of tools for automated data collection. Undertook data cleansing and processing of extensive datasets, alongside the design and management of datasets. Contributed to developing custom data models and algorithms, facilitating informed business decisions.Employed factor analysis to combine client data variables for loss and risk with in-house demographic data to employ a new variable to predict the risk level of stores with incomplete data utilizing logistic regression.Developed SAS programs to extract, transform, and load data from various sources to create and maintain reports, summaries, and other data outputs, such as manipulating data into different types, performing correlation analysis on variables to work with factor analysis, and performing logistic regression. Created a range of Power BI dashboards to help visualize complex datasets to enhance readability, and bring about trend identification for clients, for example, building dashboards with slicers to showcase site reports, and region reports that summarized site and region loss and risk data that compared to other sites and regions. Utilized Excel functions such as SUMIFS, COUNTIFS, and Pivot tables to perform exploratory data analysis, as well as using VLOOKUPS and various formatting techniques within Excel to clean and manipulate data. Show less -
Data Science StudentPenn State University Aug 2017 - Dec 2021University Park, Pennsylvania, United StatesEngineered a CountVectorizer to transform textual data into numerical representations, facilitating content categorization for a medical practice based on areas of specialty. Developed a lemmatization function to consolidate inflected word forms for NLP. Devised a classification mechanism for eye movements (e.g., right, left, straight, closed), employing data partitioning into training and validation sets. Employed PyTorch to optimize parameters and implemented a learning rate decay… Show more Engineered a CountVectorizer to transform textual data into numerical representations, facilitating content categorization for a medical practice based on areas of specialty. Developed a lemmatization function to consolidate inflected word forms for NLP. Devised a classification mechanism for eye movements (e.g., right, left, straight, closed), employing data partitioning into training and validation sets. Employed PyTorch to optimize parameters and implemented a learning rate decay strategy after each epoch. Leveraged the transfer learning model vgg16 for visualization.Performed regression testing in Python to predict values within data by handling missing values, binning values, turning categorical variables into quantitative variables, performing exploratory data analysis by utilizing correlation statistics, evaluating the model using visualization, applying polynomial regression techniques, and using R-squared, and MSE for in sample evaluation.Utilized SQL to create and query databases performing skills such as filtering, using wildcards, sorting, grouping data, using subqueries, and joining data.Analyzed COVID-19 data using R to identify trends and insights by using dplyr to clean and filter relevant columns (date, country, cases, deaths), summarized total cases and death by country, created visualizations using ggplot2 to display trends and comparisons, and split the data into training and testing sets to utilize the caret package to build a linear regression model to predict future cases. Proficient in Python, R, and Java, with hands-on expertise in utilizing the R Tidyverse, and prominent Python libraries such as Pandas, NumPy, PyTorch, TensorFlow, and Scikit-learn. Acquired skills in SQL, MongoDB, and Cypher for querying and constructing large datasets. Show less
Matt Lane Education Details
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Applied Data Science
Frequently Asked Questions about Matt Lane
What company does Matt Lane work for?
Matt Lane works for Expana
What is Matt Lane's role at the current company?
Matt Lane's current role is Data Analyst.
What is Matt Lane's email address?
Matt Lane's email address is ml****@****dex.com
What schools did Matt Lane attend?
Matt Lane attended Penn State University.
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