Statistics Graduate Level Tutor

Job Description

Statistics Graduate Level Tutor | Varsity Tutors

The Tone:
This is a contract role at Varsity Tutors, a company that transforms learning through advanced technology, AI, and learning science. The role is remote and offers the flexibility to set your own schedule while earning competitive rates. As a tutor, you will make a significant impact on graduate students’ academic success and understanding in statistics from the comfort of your home.

The TL;DR
• Role: Contract
• Location: Remote
• Pay: Up to $40 hourly
• Mission: Support graduate-level students nationally in advanced statistics to improve their academic success and understanding.
• Tech Stack: Live Learning Platform, AI-powered Tutor Copilot, R, Python

What You’ll Actually Do
• Deliver personalized online tutoring sessions to graduate-level students, either scheduled 1-on-1 or on-demand.
• Explain advanced statistical concepts such as asymptotic theory, Bayesian inference, and generalized linear models.
• Guide students through practical applications, including designing experiments, performing multivariate analysis, and implementing statistical models in software.
• Adapt teaching methods and curriculum awareness to address common challenges faced by masters and doctoral students across quantitative disciplines.
• Utilize the AI-powered Tutor Copilot for real-time instructional support, lesson generation, and engagement features.

The Must-Haves
• Background: Advanced subject mastery in graduate-level statistics, encompassing mathematical statistics, hypothesis testing theory, Bayesian inference, and regression analysis.
• Experience: Proven ability to teach and prepare students for research methodology and doctoral-level statistical analysis.
• Skills: Deep knowledge in maximum likelihood estimation, multivariate methods, experimental design, and nonparametric statistics; proficiency in R or Python for statistical computing; strong communication skills with an engaging teaching style; adeptness at adapting instruction to meet individual learning needs.
• Bonus: Familiarity with graduate statistics curricula and common student challenges, such as understanding measure-theoretic probability foundations and deriving estimator properties.