Novin Ghaffari

SETCONNECT, INC

Content Developer, Aug 2020 – present

Developed introductory courses for data analytics in Python, business statistics, and predictive analytics, designing course material, assignments, and recording parts of the courses.
Developed seminars on data science and AI for major Indian corporations and business associations.
Participated in business development strategy and planning, designing core operational tactics for future business directions.
Worked on several advisory projects, guiding major corporations on the analysis and modeling of data driven challenges, such as improving quality to reduce warranty claims, conducting market share analysis, and improving aftermarket sales profitability.

Contract Statistician, Jul 2025 – present

Outlined modeling approach for predicting symptom severity of rare genetic disorder under treatment effects from clinical trial data.
Implemented linear model, decision tree, random forest, and regression tree modeling approaches, comparing accuracy and performance to the linear model benchmark.
Guided team through the selection of the regression tree approach for client deliverable, balancing accuracy and computational complexity.
Crafted report on methodology covering background, applications to clinical trials, implementation, and model evaluation

Adjunct Professor, Oct 2021 – present

Designed course teaching public policy majors statistical methods and reasoning while introducing the federal statistical system
Structured course to balance foundational principles, breadth of exposure, and hands-on analytical experience with R
Taught the course to graduate students in public policy, teaching first principles and demonstrating computational implementation
Taught ‘Doing Data Science,’ an introductory data science course covering the basics of statistics, modeling, and common tech platforms for working professional data science master’s students.
Assisted on monthly planning meetings to determine scope and design of the data science program at SMU.

BUREAU OF TRANSPORTATION STATISTICS, USDOT

Statistician, Nov 2023 – Oct 2025

Built regression models to accurately predict passenger enplanements from TSA inspection data to improve the speed of decision-making in air passenger management and airport development strategy.
Developed schema for converting National Transportation Statistics from a spreadsheet system to a SQL-compliant database, enabling enhanced analysis by stakeholders; an external contractor previously worked on this project costing BTS >$1,000,000 with little progress.
Implemented SARIMA models for forecasting transborder freight, vehicle miles traveled, transit, and Amtrak data, enabling faster and more accurate investment decisions in the transportation sector.
Led statistical analysis of VIUS truck data, focusing on safety and autonomous technology adoption in nongovernmental trucks to inform future investment needs and strategy.
Served on an interagency committee for the NSDS-D initiative for federal statistics, developing strategies for implementation and governance models for a future NSDS system.
Originator and main lead on NSDS project, managing external contractors developing AI for the federal statistical system to address data standardization, quality control, and integration.

NULIXIR, INC

Chief of Data and Analytics, Jan 2021 – June 2023; Analytics Consultant, July 2023-Aug 2024

Conducted background research, developed reporting covering business intelligence, marketing, and clinical scientific data for nutraceuticals.
Led analysis and research on product development agreements, providing product development insights based on scientific publications to corporate clients.
Developed preliminary databases using MySQL and a data schema using ‘sqlalchemy’ Python for research and for production.
Developed API access tools in Python connecting lab scientists to PubChem and ChemSpider databases.
Advised on power calculations, design of experiments, and R shiny reporting app for internal clinical trials.

Self-Employed, June 2020 – May 2022

Worked with clients, from academia to industry, on a variety of data analysis and modeling challenges.
Performed analysis estimating genetic content of hybrid plants for Ag Biotech, Inc reducing royalties owed by client by 30%.
Advised PhD researcher on decision tree methods to better model nonlinear effects present in field data.

UNIVERSITY OF TEXAS, PhD, Statistics, Dec 2019

Conducted cross-disciplinary mathematical research for ‘optimal transportation’ topic and presented the theory, using illustrative visuals and basic examples making concepts comprehensible.
Developed several minor theoretical results and algorithmic applications for Wasserstein barycenters.

UNIVERSITY OF TEXAS, Masters of Science, Statistics, May 2014

Initiated independent research into stable distribution theory, a mathematically-challenging, lesser-known field of statistics.
Implemented MCMC routines and an FFT method for inference with stable distributions.

UNIVERSITY OF TEXAS, Bachelor of Business Administration, Finance; Minor: Supply Chain, May 2012

UNIVERSITY OF TEXAS, Bachelor of Science, Mathematics, May 2012

UNIVERSITY OF TEXAS, Bachelor of Arts, Plan II, May 2012

Experience