Statistics Graduate Level Tutor

Job Description

Statistics Graduate Level Tutor | Varsity Tutors

The Tone:
This is a contract role at Varsity Tutors, located remotely. The company develops a Live Learning Platform that leverages advanced technology, AI, and the latest in learning science to create personalized learning experiences. This role is crucial for transforming how students learn, helping them achieve their academic goals and fostering a deeper understanding of complex statistical concepts. Tutors directly contribute to better learning outcomes and a passion for the subject.

The TL;DR
• Role: Contract
• Location: Remote
• Pay: $40 hourly
• Mission: Provide personalized instruction to graduate-level students in Statistics, helping them achieve academic success.
• Tech Stack: Live Learning Platform, AI-powered Tutor Copilot, R, Python

What You’ll Actually Do
• Provide personalized 1-on-1 online instruction to graduate-level students in advanced statistics, adapting sessions to individual learning styles and needs.
• Explain complex statistical theories and derivations, including maximum likelihood estimation, posterior distribution calculations, and ANOVA decompositions.
• Guide students through practical applications like designing experiments, performing multivariate analysis, and implementing statistical models in software.
• Prepare students for research methodology and doctoral-level statistical analysis, emphasizing theoretical foundations and connections to various research applications.
• Utilize the AI-powered Tutor Copilot and other platform tools to enhance sessions, generate lessons, and save prep time.

The Must-Haves
• Background: Deep knowledge of mathematical statistics and familiarity with graduate statistics curricula, encompassing concepts like Bayesian inference, regression analysis, and nonparametric statistics.
• Experience: Capability to prepare students for research methodology and doctoral-level statistical analysis, along with experience using R or Python for statistical computing.
• Skills:
• Advanced subject mastery across mathematical statistics, including asymptotic theory, Neyman-Pearson lemma, and generalized linear models.
• Proficiency in breaking down complex derivations and calculations for likelihood functions, posterior distributions, and ANOVA.
• Ability to guide students through designing experiments, performing multivariate analysis, and constructing confidence regions.
• Strong communication skills to identify common student struggles and explain material using multiple approaches effectively.
• Competence in adapting instruction using research paper examples and proof-based exercises for masters and doctoral students.