Gis analyst Jobs in Okotoks, AB
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Gis analyst • okotoks ab
Last updated: 14 hours ago
As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-...Show moreLast updated: 30+ days ago
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare.We are known for delivering insights, products, and services that make quality care more accessibl...Show moreLast updated: 14 hours ago
From the open road to the boardroom, we offer diverse career opportunities from coast-to-coast.We are seeking an experienced and highly analytical professional to join our team as a Senior NGL Anal...Show moreLast updated: 30+ days ago
Remote R Engineer - AI Trainer
SuperAnnotateOkotoks, Alberta, CARemote
Full-time
- New!
Associate Clinical Programs Analyst (Registered Nurse / LPN) - RN
MCKESSONFOOTHILLS, Alberta, CanadaFull-time
Senior Analyst
Superior PropaneAlberta, CanadaFull-time
- Winnipeg, MB (from $ 78,995 to $ 155,415 year)
- Montreal, QC (from $ 86,477 to $ 155,415 year)
- Truro, NS (from $ 63,408 to $ 142,946 year)
- Chilliwack, BC (from $ 65,863 to $ 139,913 year)
- White Rock, BC (from $ 67,794 to $ 139,913 year)
- Waterloo, ON (from $ 96,641 to $ 137,507 year)
- Cambridge, ON (from $ 92,278 to $ 137,507 year)
- Mississauga, ON (from $ 97,400 to $ 132,731 year)
- Halifax, NS (from $ 73,976 to $ 130,691 year)
- Vaughan, ON (from $ 96,418 to $ 130,650 year)
Remote R Engineer - AI Trainer
SuperAnnotateOkotoks, Alberta, CA30+ days ago
Job type
- Full-time
- Remote
Job description2+ years of hands-on experience using R for data analysis, statistics, or data science work. Strong proficiency in R programming, including data wrangling, functional programming patterns, and writing reusable functions or packages. Solid grounding in applied statistics, including regression, inference, and model validation, with practical experience implementing these methods in R. Experience building end-to-end analyses in R that include data cleaning, exploratory analysis, modeling, and visualization. Familiarity with common R ecosystems such as tidyverse, data.table, and ggplot2, and the ability to choose appropriate tools for a given task. Professional experience in a data-focused role such as data scientist, statistician, quantitative analyst, or similar. Minimum Bachelor’s degree in Statistics, Mathematics, Computer Science, or a closely related quantitative field. Significant experience using large language models (LLMs) to assist with coding, analysis design, and code review in R. Excellent English writing skills with the ability to document analyses and explain complex statistical ideas clearly to non-experts. Previous experience with AI data training or model evaluation is strongly preferred, and Minimum C1 English proficiency is required.
As a remote, hourly paid R Engineer, you will review AI-generated responses and generate high-quality R and data-analysis-focused content, evaluating the reasoning quality and step-by-step problem-solving behind each solution. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in statistical methodology or data-wrangling workflows; fact-check analytical results; write expert-level explanations and model solutions that demonstrate correct use of R; and rate and compare multiple AI responses based on correctness and reasoning quality. This contract role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation model labs, directly helping to improve the world’s premier AI models.
Key Responsibilities :
- Develop AI Training Content : Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
- Optimize AI Performance : Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
- Ensure Model Integrity : Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
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