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 leverages advanced technology, AI, and learning science to create personalized learning experiences. This role allows tutors to make a significant impact on students’ academic success and understanding, fostering better outcomes and a passion for learning through customized instruction.

The TL;DR
• Role: Contract
• Location: Remote
• Pay: Up to $40 hourly
• Mission: Provide personalized, impactful online tutoring to graduate-level statistics students using an advanced learning platform.
• Tech Stack: Live Learning Platform, AI-powered Tutor Copilot, R, Python

What You’ll Actually Do
• Instruction: Deliver personalized 1-on-1 online tutoring to individual students studying graduate-level statistics.
• Curriculum Guidance: Guide students through advanced statistical concepts such as maximum likelihood estimation, Bayesian inference, and asymptotic theory, supporting doctoral-level statistical analysis.
• Adaptive Teaching: Adapt instructional methods using R or Python, research paper examples, and proof-based exercises to meet the specific learning needs and styles of masters and doctoral students.
• Platform Engagement: Utilize the AI-powered Tutor Copilot for real-time instructional support, lesson generation, and engagement features to enhance tutoring sessions.
• Schedule Management: Set your own flexible hours and accept on-demand instant tutoring requests, while Varsity Tutors handles student matching, logistics, and payments.

The Must-Haves
• Background: Advanced academic background demonstrating deep knowledge of mathematical statistics, including maximum likelihood estimation, hypothesis testing theory, Bayesian inference, regression analysis, multivariate methods, and nonparametric statistics, capable of explaining asymptotic theory and generalized linear models.
• Experience: Proven ability to break down complex statistical derivations like likelihood function and posterior distribution calculations, guide students through designing experiments and multivariate analysis, and implement statistical models in software.
• Skills: Strong communication and an engaging teaching style; ability to adapt instruction to meet individual learning needs; familiarity with graduate statistics curricula and common student challenges; proficiency in R or Python for statistical computing; aptitude for identifying conceptual struggles and explaining material using multiple approaches.