Statistics Graduate Level Tutor

Job Description

Statistics Graduate Level Tutor | Varsity Tutors

The Tone:
This is a contract role at Varsity Tutors, offering a remote opportunity for Statistics Graduate Level Tutors. Varsity Tutors builds an advanced learning platform leveraging technology, AI, and learning science to create personalized educational experiences. In this role, you will significantly impact students’ academic success and understanding by providing expert guidance in graduate-level statistics from the comfort of your home.

The TL;DR
• Role: Contract
• Type: Flexible Schedule
• Location: Remote
• Pay: $40 hourly
• Mission: To support thousands of students nationally in statistics, helping them achieve academic success and understanding.
• Tech Stack: Live Learning Platform, AI-powered Tutor Copilot, R, Python

What You’ll Actually Do
• Provide personalized, individual instruction to students in graduate-level statistics.
• Explain complex statistical concepts, theories, and derivations, such as likelihood functions, posterior distributions, Neyman-Pearson lemma, and asymptotic theory.
• Guide students through problem-solving, including designing experiments, performing multivariate analysis, constructing confidence regions, and implementing statistical models in software.
• Adapt instruction to align with graduate statistics curricula, addressing common challenges like measure-theoretic probability and interpreting complex model outputs.
• Prepare students for advanced statistical applications in research methodology, biostatistics, econometrics, machine learning, and doctoral-level analysis.

The Must-Haves
• Background: A deep, graduate-level understanding of advanced statistics, encompassing mathematical statistics, maximum likelihood estimation, sufficient statistics, hypothesis testing theory, Bayesian inference, regression analysis, multivariate methods, experimental design, and nonparametric statistics.
• Experience: Proven ability to break down complex concepts and guide students through sophisticated statistical problems, coupled with familiarity with graduate statistics curricula and the challenges master’s and doctoral students face across quantitative disciplines.
• Skills: Advanced subject mastery in areas like generalized linear models and ANOVA decompositions; conceptual teaching with an emphasis on theoretical foundations; adaptive instruction using R or Python statistical computing and research paper examples; strong communication and an engaging teaching style to identify and address student struggles.