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, aiming to revolutionize learning through advanced technology, AI, and the latest learning science to create personalized educational experiences. This role is crucial for significantly impacting graduate students’ academic success and understanding in statistics, fostering better outcomes and a passion for learning.

The TL;DR
• Role: Contract
• Location: Remote
• Pay: Up to $40 hourly
• Mission: This person solves the problem of helping Statistics Graduate Level students achieve academic success and understanding through personalized instruction.
• Tech Stack: R, Python

What You’ll Actually Do
• Instruction: Provide personalized, individual online instruction to Statistics Graduate Level students.
• Conceptual Teaching: Break down complex statistical concepts, such as likelihood function derivations and ANOVA decompositions, for graduate students.
• Research Preparation: Prepare students for advanced research methodology and doctoral-level statistical analysis.
• Model Guidance: Guide students through designing experiments, performing multivariate analysis, and implementing statistical models in software.
• Adaptive Learning: Adapt instruction using R or Python statistical computing, research paper examples, and proof-based exercises to support masters and doctoral students.

The Must-Haves
• Background: Advanced subject mastery in mathematical statistics, essential for teaching graduate-level students.
• Experience: Proven ability to explain complex statistical concepts, prepare students for doctoral-level analysis, and adapt teaching methods to individual learning needs in a graduate context.
• Skills: Deep knowledge of mathematical statistics including maximum likelihood estimation, Bayesian inference, regression analysis, asymptotic theory, and generalized linear models; proficiency in conceptual teaching and problem-solving for advanced topics; strong communication and adaptive teaching skills; familiarity with graduate statistics curricula; and ability to use R or Python for statistical computing.