Thomas T. John, Ph.D.

Statistician and data analyst with 20+ years of combined experience in applied industry research, independent consulting, and university-level instruction. Expertise spans predictive modeling, data automation, survey analytics, biostatistics, and statistical computing across a broad range of sectors — from Fortune 500 telecommunications and technology firms to global logistics, healthcare, automotive, and manufacturing clients. Known for rapidly acquiring new technical environments and translating complex analytical findings into clear, actionable insights for diverse stakeholders at every level of technical sophistication.

What distinguishes this body of work is not breadth alone, but depth of ownership: analytical pipelines built from scratch, methodologies introduced and operationalized without a roadmap, and solutions driven to adoption through organizational friction. Published clinical research, globally deployed segmentation tools, and peer-reviewed mathematical contributions sit alongside practical automation systems and real-time consulting interventions — reflecting a career in which rigorous statistical thinking has consistently met the demands of high-stakes, real-world problems. Currently serving as Assistant Teaching Professor of Statistics at Syracuse University while maintaining an active independent consulting practice.

Hard Skills

• Statistical Methods: Regression (OLS, Logistic, LASSO, Elastic Net), GLMs, Time Series, Discriminant Analysis, CART, Random Forest, Factor Analysis, Structural Equation Modeling, Survival Analysis, Discrete Choice / Conjoint Analysis, Maximum Difference Scaling, Survey Weighting
• Software & Tools: SAS (SAS/STAT, SAS/QC, SAS/GRAPH; installation verification in FDA-regulated environments), R (including PostgreSQL integration via RPostgres/DBI), SPSS, JMP, Minitab, MATLAB, Maple
• Programming: Visual Basic / Office-VBA, R/Shiny, Perl, Fortran, HTML, JavaScript, CSS
• Platforms: Sawtooth CBC/HB (Hierarchical Bayes Conjoint), WeBWorK, Gradescope
• Reporting & BI: Statistical reporting automation, dashboard design, data workflow development

Soft Skills

• Communication: Translating complex methodology and findings for non-technical audiences across corporate, clinical, and academic settings
• Adaptability: Consistent track record of rapidly acquiring unfamiliar technical tools and environments to deliver working solutions under deadline
• Collaboration: Cross-functional engagement with diverse client and research teams spanning market research, healthcare, engineering, and academia
• Mentoring: Career-direction guidance for undergraduates (actuarial pathways, GitHub, LinkedIn presence) and professional positioning for graduate students (translating teaching assistantship experience into industry framing)

KS&R (Knowledge Systems & Research) Inc. — 2004–2010; Independent Practice — 2010–Present

Clients spanning telecommunications, technology, logistics, healthcare, automotive, and manufacturing — including AT&T, FedEx, IBM, Microsoft, American Cancer Society, Welch Allyn, ADP, Cox Automotive, MTD, Spectrum/TWC

• Closing competitive gaps → Brought & incorporated rival-proven methodology: Introduced Maximum Difference Scaling (MaxDiff) to the organization — a method already used by competing analytic firms. Secured internal buy-in, developed proposal language for client pitches, built survey logistics, analysis workflows, and presentation formats from the ground up.
• Brittle legacy → powerful, efficient pipeline: Replaced a manually-patched Sawtooth-dependent experimental design process — where constraint violations required hand-correction across every project — with a constraint-capable system built on SAS/QC (PROC FACTEX, OPTEX). Designed full downstream delivery: Excel workbooks (one sheet per choice task) for client review teams, and HTML/CSS/JavaScript pages for field programming teams. Automated back-end construction of Sawtooth-required .cho files by merging design structure with collected sample data, enabling CBC/HB analysis without Sawtooth’s front-end.
• Innovative solo build → adoption pushed through friction: Envisioned and single-handedly built a VBA-based reporting automation platform that replaced a multi-person war-room assembly process — where assistants hand-transcribed significance letters and numbers from printed SPSS crosstabs into PowerPoint page by page. Drove adoption through organizational resistance to deliver a fully automated SPSS-to-PowerPoint pipeline.
• Mission-critical and complex → global segmentation with high stakes: Led market segmentation and classification modeling for a multi-million dollar global B2B engagement, navigating client anxiety about organizational disruption and execution complexity across a geographically dispersed salesforce. Delivered a multilingual Excel-based classification tool for field use across international markets.
• Western theory, Asian markets → customer equity modeling across Asia-Pacific: Applied the Rust, Zeithaml & Lemon customer equity framework (brand loyalty, value equity, retention equity as latent constructs) to a FedEx APAC engagement spanning Thailand, Vietnam, Hong Kong, and surrounding markets using canonical correlation and structural equation modeling.
• Obsolete platform, tight deadline → crisis solution built from scratch: Rapidly designed and delivered a working analytical solution under deadline pressure using an unfamiliar legacy platform, with no prior exposure to the environment.
• Go-to across teams → survey design, weighting, and proposal language firm-wide: Served as the internal methodological authority on survey question design (bias-free phrasing, rating/ranking exercises, feature distinction), stratified sampling, and weighting methodology — regularly consulted by research analysts and project managers across all client teams for both proposal language and execution guidance.

Additional engagements have spanned biostatistical analysis for medical device validation studies, R/Shiny application development, higher education persistence research, and cross-disciplinary academic consulting. Device validation work for Welch Allyn included Bland-Altman plots produced using customized SAS/GRAPH code that appeared in published clinical research summaries used in product documentation, still publicly available. R/Shiny work involved building a web portal alongside a maintained Excel simulator, including security and credential management for access by particular team members only. A university College of Engineering cohort study yielded actionable findings through data slicing via pivot tables and cross-tabulation — without formal modeling — surfacing patterns that had been overlooked internally.

• Full Scholarship for Graduate Study, Syracuse University
• Phi Beta Kappa (Sigma Chapter of NY, 1995); Golden Key National Honor Society (1994); Pi Mu Epsilon (NY Alpha Alpha, 1996)
• Presidential Award for Outstanding Freshmen, Queens College (1993); Dean’s List every semester 1992–1996

• Marwaha S., John T., et al. User Preference and Workflow Evaluation of a Vital Signs Monitor. Advances in Human Factors and Ergonomics in Healthcare, AHFE 2020, Springer.
• Neely J., John T., et al. Impact of Single Sign-On Adoption in an Assessment Triage Unit. Journal of Nursing Administration, Vol. 50(3), 2020.
• Alpert B., John T., et al. Accurate Blood Pressure During Patient Arm Movement. Blood Pressure Monitoring, Vol. 24, 2019.
• John T. & Chen P. ℒ¹-limit of Trimmed Sums of Order Statistics. Communications in Statistics — Theory and Methods, Vol. 37(16), 2008.
• John T. & Chen P. Selection of the Best from Log-normal Populations Using Type-II Censored Data. Sequential Analysis, Vol. 25, 2006.
• John T. & Chen P. Log-normal Selection with Applications to Lifetime Data. IEEE Transactions on Reliability, Vol. 55(1), 2006.
• John T., Jagannathan R., & Velu R. A Test of Linear Beta Pricing When Error Covariance Matrix is Diagonal. Manuscript in Preparation.

• Referee: Discrete Event Dynamic Systems; Sequential Analysis; Simulation Modelling: Practice & Theory; Journal of Business Research
• Invited presentations, Society of Clinical Research Associates (NY Chapter): statistical methods for clinical researchers (2013–2023); including invited lecture at SOCRA 24th Annual Conference, Denver, September 2015
• Invited talk, CNY Biotech Accelerator: Statistics/Sample Size/Data Methods (2017)
• Invited Chair, Session on Statistics, AMS-MAA Joint Meetings, Phoenix (2004)
• Leveraging Primary Market Research Synchronized with Data Mining Models, International Conference on Business Data Mining, C.R. Rao Institute of Mathematics & Statistics, University of Hyderabad, December 2008
• Guest lectures, MAR 600 (Marketing Analytics), Whitman School of Management: Supervised & Unsupervised Machine Learning with R Illustrations (2015); CART & Random Forest — Applications of Classification to Marketing (2013)
• Guest lectures, MAT 752 (Statistical Ranking & Selection), Department of Mathematics: Selection Procedures for Log-Location-Scale Populations (2015, 2016)
• Contributed to reconstruction and preparation of Reinsel & Velu, Multivariate Statistical Analysis (2nd ed., Springer), supporting posthumous continuation of the work following Reinsel’s passing
• Rенée Crown University Honors Capstone Thesis advisor (Grace Mehr), Syracuse University, Spring 2020
• Women in Science and Engineering (WiSE) portfolio reviewer, Syracuse University: June 2020, June 2021
• Dissertation committee member (Benjamin Cortese), Syracuse University, 2015
• Ph.D. comprehensive examination committee (Krzysztof Herman), Whitman School of Management, Syracuse University, Summer 2013