Statistics Tutor na SpaceXAI

Remoto - Remote

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The role of Statistics Tutor at SpaceXAI involves providing high‑quality inputs, labels, and annotations to advance AI technologies. Tutors will collaborate with technical teams to train models, refine annotation tools, and select challenging statistical problems for model performance. The position is remote and may be offered as full‑time, part‑time, or contractor, with compensation ranging from $45 to $75 per hour for U.S. candidates. Candidates are expected to hold advanced degrees or competitive honors in statistics or related fields and demonstrate strong communication and analytical skills.

Salary

USD 45 - 75/hour

Requirements

Skills

  • Must have either a Master’s or PhD in Statistics (or Mathematics with a specialization in statistics or probability) or a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition.
  • Proficiency in reading and writing, both in informal and professional English.
  • Strong ability to navigate various information resources and databases.
  • Outstanding communication, interpersonal, analytical, and organizational capabilities.
  • Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material.
  • A strong passion for and commitment to technological advancements and innovation.

Responsibilities

  • Use proprietary software applications to provide input/labels on defined projects.
  • Support and ensure the delivery of high-quality curated data.
  • Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.
  • Interact with the technical staff to help improve the design of efficient annotation tools.
  • Choose problems from statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modeling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses.
  • Interpret, analyze, and execute tasks based on given instructions.

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