Statistics Graduate Level Tutor

Job Description

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 that uses advanced technology, AI, and learning science to create highly personalized educational journeys. This role is crucial for providing expert guidance in complex graduate-level statistics, helping students achieve academic success and deeper understanding, and fostering a passion for learning.

The TL;DR
• Role: Contract
• Location: Remote
• Pay: Up to $40 hourly
• Mission: This person solves the problem of students needing expert guidance in graduate-level statistics by providing tailored, personalized instruction that supports their learning goals.
• Tech Stack: AI-powered Tutor Copilot, R, Python, Live Learning Platform

What You’ll Actually Do
• Instruct: Provide personalized, one-on-one or on-demand instruction to individual students in graduate-level statistics.
• Explain: Clearly explain advanced statistics concepts like asymptotic theory, Neyman-Pearson lemma, and generalized linear models, breaking down complex derivations and decompositions.
• Guide: Guide students through designing experiments, performing multivariate analysis, constructing confidence regions, and implementing statistical models in software.
• Prepare: Prepare students for research methodology and doctoral-level statistical analysis, emphasizing theoretical foundations and research applications.
• Adapt: Adapt instruction using statistical computing tools, relevant research paper examples, and proof-based exercises to support masters and doctoral students.

The Must-Haves
• Background: Graduate-level expertise and deep knowledge in core statistics topics and theories relevant to advanced academic study.
• Experience: Experience tutoring or teaching advanced statistical concepts to graduate-level students, including the ability to guide through complex derivations and software implementation.
• Skills: Deep knowledge of mathematical statistics, maximum likelihood estimation, hypothesis testing theory, Bayesian inference, and regression analysis; proficiency in statistical computing tools like R or Python; strong communication skills with an engaging teaching style.