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Graduate Teaching Assistant Resume

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Orlando, FL

SUMMARY:

  • Highly motivated and curious graduate student with three years of relevant professional experience. Proficient in computational statistics, data analytics and machine learning techniques. Strong communication skills with a confident and amiable personality.
  • Experienced (3+ years): SAS, R, SQL, Microsoft Office
  • Proficient (1 - 3 years): Python, VBA, Linux, Matlab, Applaud® (ETL software)
  • Actuarial Exams (passed): Probability, Financial Mathematics, Models in Financial Economics
  • Relevant Topics of Expertise: time series, experimental design, linear and logistic regression, dimension reduction, forecasting, data mining, predictive analytics, Machine Learning/ Statistical Algorithms: k-NN, support vector machines, linear and logistic regression, decision trees, discriminant analysis, neural networks, clustering, naïve Bayes

PROFESSIONAL EXPERIENCE:

Confidential, Orlando,FL

Graduate Teaching Assistant

Responsibilities:

  • Instructed semester-long undergraduate classes of 50-70 students for an introductory statistics course
  • Created lectures, quizzes and exams as well as provided weekly office hours for tutoring

Confidential, Raleigh, NC

Analytical Consulting Intern

Responsibilities:

  • Utilized similarity techniques to create a data cleansing algorithm that fills in missing temperature time series data
  • Researched statistical theory for electrical load forecasting methods and updated documentation for SAS software

Confidential, Chicago, IL

IT Consultant

Responsibilities:

  • Produced data conversions to successfully migrate 18 different legacy systems for an Oracle R12 implementation
  • Developed an automated reporting processes which identified duplicates, anomalies, missing and invalid data
  • Delivered analytical solutions for data consolidation, profiling, analysis and cleansing using SQL and Applaud®

Confidential, Jacksonville,FL

Actuarial Analyst

Responsibilities:

  • Designed and built actuarialtoolusing VBA and SAS to forecast a medical loss ratio rebate
  • Collaborated with co-workers to identify and solve issues with claim and premium data using SQL
  • Utilized statistical techniques and industry knowledge to set monthly financial reserves for claim liabilities

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