Biography

Lisa

Master of Science, 2015
Computational Mathematics
Duquesne University, Pittsburgh, PA

Teacher Certification, 2012
Mathematics 7-12
Robert Morris University, Pittsburgh, PA

Bachelor of Science, 1994
Scientific and Technical Communication
Bowling Green State University,
Bowling Green, OH

My Career Goals

My professional goal brings together my expertise and enthusiasm for computer science, statistics, and mathematics; my desire to solve problems that benefit people, organizations, or society; and my conviction to embrace challenges and to continue learning. For the past two years, I have taught Business Statistics courses as an Adjunct Professor in Duquesne’s School of Business. I am interested in a change to full-time employment in data management and/or data analysis.

I bring a set of core teaching, communication, and programming skills as well as professionalism, dedication, and perseverance to everything I do. I am an enthusiastic, independent learner and worker who values constructive criticism and welcomes opportunities to collaborate with peers. I gravitate toward intellectual challenges and am prone to try new approaches or techniques in my work. Thank you for taking the time to evaluate my qualifications. Feel free to contact me at the phone number or email above if you have a need for someone with my skills. I look forward to hearing from you.

Education and Experience

My education includes a bachelor’s degree in Scientific and Technical Communication, a PA State Teacher Certification in 7-12 Mathematics, and a master’s degree in Computational Mathematics. My research for my Master’s thesis involved collaborating with a professor from the Educational Foundations and Leadership department to explore the relationship between School Performance Profile (SPP) scores and family income. Writing my thesis required working with two disparate sources of data to develop a method for joining them for analysis, evaluating different regression models to find the best fit for the data, and researching underlying socioeconomic issues that would explain possible reasons for the relationship between income and SPP scores.

As a graduate student in Computational Mathematics, I refined my problem-solving skills and developed new skills in statistics and data science. My research for my Master’s thesis involved collaborating with a professor from the Educational Foundations and Leadership department to explore the relationship between School Performance Profile (SPP) scores and family income. Writing my thesis required working with two disparate sources of data to develop a method for joining them for analysis, evaluating different regression models to find the best fit for the data, and researching underlying socioeconomic issues that would explain possible reasons for the relationship between income and SPP scores.

In a Business Intelligence course, I acquired general data mining skills and worked extensively with SSIS, SSAS, DQS to complete an ETL project with SQL Server. I extracted data from a variety of sources, transformed the data according to project specifications, and loaded the data into a data warehouse for analysis. Throughout my program, I focused my studies on statistics and computer science and finished my master’s degree with a solid foundation of computational skills including database and data warehouse programming with SQL, server-side programming with JSP, software engineering with Java, data visualization, ANOVA, regression analysis, experimental design, and statistical computing.

As a business analyst intern, I assisted higher-level analysts on a variety of market research projects, which involved creating graphs, data summaries, and regression model reports for a new brand volume forecast and an analysis of out of stock SKUs. To fulfill my responsibilities, I wrote SAS procedures and macros to organize and summarize the data and to run models. In addition, I wrote visual basic scripts in Excel to perform calculations and to create report summaries and charts automatically, which made data preparation more efficient and less prone to error.

As an adjunct professor of business statistics, I have had the opportunity to teach descriptive statistics, probability, one- and two-sample t-tests, chi-square test for independence, and regression analysis for five semesters. I am comfortable programming in VB, R, SAS, Python, and SQL and am resourceful in learning new constructs and techniques as well as other programs or languages.

Finally, I continue to refine and extend my knowledge of data science and machine learning by taking courses through edX and Coursera. You will find more detailed information on my resume and online portfolio. Thank you for taking the time to review my qualifications. I would welcome the opportunity to learn more about new career opportunities and to discuss my experience with you in person. Please contact me at the phone number or email listed above.