This document is a resume for Joseph Teitelman, who has extensive experience and skills in statistics, data analysis, and data science. He has over 25 years of experience with SAS and over 20 years with SPSS. His statistical experience includes univariate, multivariate, parametric, and nonparametric methods as well as regression, survival analysis, sampling designs, and machine learning. He has worked as a statistician, data analyst, consultant, teacher, and tutor. His education includes an M.S. in sociology from Duke University and coursework towards an M.S. in biostatistics from UNC-Chapel Hill. He recently completed two online courses from MIT in analytics and probability theory.

1. STATISTICIAN • DATA SCIENTIST/ANALYST • MARKETING RESEARCH ANALYST
Joseph Teitelman
964 Tulip Rd. SE, Rio Rancho, NM 87124
505.891.5399
joe.teitelman@gmail.com
STATISTICAL METHODS/COMPUTING SKILLS
• Univariate/multivariate, parametric/nonparametric, descriptive/inferential
• Generalized, linear, and mixed models: models for discrete/count/continuous outcomes,
including linear, logistic and Poisson regression
• Survival analysis: Proportional (Cox) Hazards models, parametric models
• Survey Research methods: sample size/power calculations, economic designs, SRS,
stratified, cluster and multistage sampling designs
• Big Data/Machine Learning methods
• Marketing research methods and econometric methods
• Familiarity with numerous other methods
• R (1+ yrs) • SAS (25+ yrs) • SPSS (20+ yrs) • MySQL (6+ months)
• MS Office (Word, Excel, PowerPoint, Access)
PROFESSIONAL EXPERIENCE
Mathematics/Statistics Tutor, Independent Contractor April 2007 – Present
• Tutor college and high school level students in mathematics and statistics courses.
Quality Control Data Statistician, Kos Pharmaceuticals, Hollywood, FL Oct 2006 – March 2007
• Hired for a six-month period to use SAS to analyze stability data for a new drug.
• Employed mixed-effects and regression methods to perform the analyses.
Marketing Research Consultant, PGA of America, Palm Beach Gardens, FL Sept 2005 – Aug 2006
• Hired primarily to help the research team (which lacked statistical expertise)
to employ scientifically sound statistical methods.
• Used survey sampling methods to assist in the development of demographic
profiles of PGA members.
Mathematic/Statistics Teacher, WAJ Central School, Windham, NY Aug 2003 – June 2005
• Taught secondary level statistics, calculus, algebra, and geometry courses.
Statistician, OPC Area Program, Chapel Hill, NC Jan 1997 – Dec 2002
• Utilized survey sampling methods to assess patient outcomes and treatment
modality preferences.
• Generated $150,000+ in otherwise lost revenues, based upon an internal audit
of OPC business practices relative to Medicaid claims data.
• Collaborated with management with the goal of allocating scarce resources to
treatment modalities yielding the most efficacious outcomes.
Tutor, Sylvan Learning Center, Chapel Hill, NC July 1990 – Jan 1994
• Provided remedial instruction to secondary-level students in various subjects.
Mathematics Teacher, Griswold High School, Griswold, CT Aug 1983 – June 1987
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2. EDUCATION
The University of North Carolina at Chapel Hill, NC Jan 1992 – May 1997
• Completed all courses required of M.S. degree students in the Department
of Biostatistics.
• Teaching Assistant for one graduate level statistics course.
Duke University, Durham, NC Aug 1986 – Oct 1990
• Master’s degree in sociology; specialized in (a) quantitative/statistical methods,
and (b) the sociology of crime, deviance and the law.
• Scored 760/800 on the quantitative section of the GREs, 680/800 on the
analytical section of the GREs and 600/800 on the verbal section of the GREs.
• Teaching Assistant for two graduate level statistics courses, and received
outstanding evaluations from each course’s students.
University of Connecticut, Storrs, CT Sept 1979 – May 1983
• Bachelor’s degree in mathematics and mathematics education.
RECENT COURSE WORK
Earned certificates of successful completion for two MIT online courses Feb 2015 – June 2015
• The Analytics Edge
- Topics included: Linear and Logistic Regression, Trees (including CART and
Random Forests), Text Aanalytics, Clustering Techniques, Visualization, Linear
and Integer Optimization. Course material was taught from a Machine
Learning perspective
• Probability Theory
- The theoretical underpinnings of mathematical statistics
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