Online Statistics Graduate Level Tutor

Job Description

Online Statistics Graduate Level Tutor | Varsity Tutors

The Tone:
This is a freelance position at Varsity Tutors, located remotely. Varsity Tutors is a live learning platform that connects thousands of students with expert educators nationwide. As an independent contractor, you will provide online instruction in Statistics at the Graduate Level, making a significant impact on students’ academic success and understanding. This role offers the flexibility to set your own hours and teach from anywhere using a purpose-built learning platform.

The TL;DR
• Role: Freelance
• Type: Contract
• Location: Remote
• Pay: $40 hourly
• Mission: Provide expert online instruction to graduate-level students in statistics, enhancing their academic success and understanding.
• Tech Stack: R, Python

What You’ll Actually Do
• Provide personalized online instruction to graduate-level students in Statistics, covering advanced topics and research methodology.
• Explain complex statistical concepts, including asymptotic theory, the Neyman-Pearson lemma, and generalized linear models.
• Guide students through intricate derivations such as likelihood functions, posterior distributions, and ANOVA decompositions.
• Prepare masters and doctoral students for research methodology and advanced statistical analysis relevant to their fields.
• Adapt instruction using statistical computing tools like R or Python, real-world research examples, and proof-based exercises.

The Must-Haves
• Background: Deep knowledge of mathematical statistics, including maximum likelihood estimation, sufficient statistics, hypothesis testing theory, and Bayesian inference.
• Experience: Experience supporting masters and doctoral students across various quantitative disciplines, guiding them through complex statistical analysis.
• Skills:
• Proficiency in regression analysis, multivariate methods, experimental design, and nonparametric statistics.
• Ability to break down intricate derivations and guide students through designing experiments, performing multivariate analysis, and implementing statistical models in software.
• Familiarity with graduate statistics curricula and common student challenges, such as measure-theoretic probability foundations and interpreting complex model outputs.
• Strong communication skills and an engaging teaching style, with the ability to adapt instruction to individual learning needs and styles.