Online Statistics Graduate Level Tutor

Job Description

Online Statistics Graduate Level Tutor | Varsity Tutors

The Tone:
This is a contract role at Varsity Tutors, located remotely. Varsity Tutors operates a Live Learning Platform, dedicated to revolutionizing learning through advanced technology, AI, and the latest in learning science. The company creates personalized educational experiences by specializing in matching students with ideal tutors, fostering better outcomes, and igniting a passion for learning. As a tutor on this platform, you will provide customized instruction, making a significant impact on students’ academic success and understanding from the comfort of your home.

The TL;DR
• Role: Contract
• Type: Contract
• Location: Remote
• Pay: $40 hourly
• Mission: This person provides personalized, graduate-level statistics instruction across various quantitative disciplines to help masters and doctoral students achieve their academic goals and enhance their understanding nationwide.
• Tech Stack: R, Python, AI-powered Tutor Copilot, Live Learning Platform

What You’ll Actually Do
• Provide: Provide personalized, one-on-one online tutoring, including instant tutoring requests, to graduate-level students in statistics.
• Instruct: Instruct on advanced statistical concepts such as mathematical statistics, maximum likelihood estimation, Bayesian inference, regression analysis, multivariate methods, experimental design, and hypothesis testing theory, including asymptotic theory, Neyman-Pearson lemma, and generalized linear models.
• Guide: Guide students through complex problem-solving by breaking down likelihood function derivations, posterior distribution calculations, ANOVA decompositions, and constructing confidence regions.
• Facilitate: Facilitate the design of experiments, performance of multivariate analysis, and implementation of statistical models in software, emphasizing theoretical foundations and connections to biostatistics, econometrics, and machine learning.
• Support: Support masters and doctoral students across quantitative disciplines by adapting instruction using R or Python statistical computing, research paper examples, and proof-based exercises, while also preparing them for research methodology and doctoral-level statistical analysis.

The Must-Haves
• Background: Deep knowledge and advanced subject mastery of mathematical statistics, including areas like maximum likelihood estimation, Bayesian inference, and hypothesis testing theory, coupled with familiarity with graduate statistics curricula and common challenges.
• Experience: Demonstrated ability to explain complex theoretical concepts such as asymptotic theory and the Neyman-Pearson lemma, break down likelihood function derivations, and guide students through designing experiments, performing multivariate analysis, and implementing statistical models in R or Python.
• Skills: Exceptional conceptual teaching skills for advanced statistical topics, strong problem-solving capabilities, and effective communication with a friendly, engaging teaching style that adapts to individual learning needs.