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Data Annotation For Ai Jobs in Quebec (NOW HIRING)

Solid understanding of star schemas, data warehousing concepts, and preparing data for consumption by both humans and AI models. Experience & Soft Skills * Experience: 3-5+ years in a Data Analytics ...

Establish standards and best practices for data modeling, integration, transformation, quality, governance, cataloging, lineage, and security. * Design AI-ready architectures that support advanced ...

Own data science initiatives end-to-end from problem framing through production deployment and ... Contribute to documentation and auditability standards for production AI systems Stakeholder ...

This includes establishing lifecycle controls for AI systems to address risks related to data usage, model integrity, bias, and operational resilience,ensuring risks are proactively identified ...

This includes establishing lifecycle controls for AI systems to address risks related to data usage, model integrity, bias, and operational resilience,ensuring risks are proactively identified ...

Set the bar for HIPAA, PHI, and AI governance. Classification at ingestion, field-level access controls, infrastructure-level scrubbing, vendor data governance, training-data lineage, and consent ...

Build scalable pipelines for data preprocessing, feature engineering, and model training. * Optimize AI frameworks to improve inference speed, reduce latency, and lower compute costs. * Integrate AI ...

New

The Data & Analytics group is looking for a Data Architect with, BI and AI expertise who will be providing consulting services to our customers. The candidate * Is a senior Data architect that can ...

... for prototyping and implementing AI-powered solutions Solid SQL skills and experience querying data warehouses (Snowflake experience is a plus) Familiarity with at least one end-to-end ML platform ...

Practical experience with LLM APIs and tools (OpenAI, Anthropic Claude, or similar) for prototyping and implementing AI-powered solutions * Solid SQL skills and experience querying data warehouses ...

Posted today

Practical experience with LLM APIs and tools (OpenAI, Anthropic Claude, or similar) for prototyping and implementing AI-powered solutions * Solid SQL skills and experience querying data warehouses ...

Posted today

Practical experience with LLM APIs and tools (OpenAI, Anthropic Claude, or similar) for prototyping and implementing AI-powered solutions * Solid SQL skills and experience querying data warehouses ...

Showing results 41-60

Data Annotation For Ai information

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.
What are popular job titles related to Data Annotation For Ai jobs in Quebec? For Data Annotation For Ai jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Data Annotation For Ai jobs in Quebec look for? The top searched job categories for Data Annotation For Ai jobs in Quebec are:
Infographic showing various Data Annotation For Ai job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Data & Trust Manager, Privacy & AI

TELUS

Montreal, QC • On-site

Other

Posted 29 days ago


TELUS rating

8.2

Company rating: 8.2 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

23rd of 97 rated telecommunications companies


Job description

Description

Join our team

The TELUS Data & Trust Office provides world-class, innovative data solutions to TELUS. We partner with teams across the organization to advance our corporate priorities, support innovation and ultimately deliver on our promise to safeguard our customer's privacy and to earn and maintain their trust.

Our team takes pride in earning a reputation for being innovative thought-leaders, strategic business partners and subject-matter experts in privacy, responsible artificial intelligence and data governance. Compliance with the law is just our starting point, as we passionately pursue opportunities to demonstrate respect for our customers and their data through transparent, robust, and ethical data practices.

The impact you'll make and what we'll accomplish together

As the Senior Data & Trust Manager, Privacy & AI, supported by the Director, Data Strategy & Partner Services, you will materially influence the ongoing development of TELUS' business innovation focused on becoming a trusted partner to the business to enable initiatives that meet our rigorous data, privacy, security and ethical standards.

Your work will enable your business units' initiatives by building a thriving and respectful data program and being a champion for data, trust and innovation. You will advocate for TELUS' Trust Model as the fundamental driver for all of our decisions around data, recognizing how critical customer and team member trust is to TELUS' mission. In doing so, you will be instrumental in advancing our reputation for being trustworthy, using a responsible human-centric approach to ensure that we use data to deliver remarkable business and social outcomes, always in a manner that demonstrates TELUS' commitment to putting our customers and communities first.

What you'll do 
  • Support TELUS' B2C business units (including Smart Home, Smart Cities, Smart Buildings, 5G Innovation) on strategic initiatives to deploy or leverage data and technology responsibly and ethically by providing expert advice and counsel to execute on TELUS' data commitments

  • Educate and advise business units on new or existing data uses and implementation of ethical technologies

  • Lead innovative strategies and creative solutions to de-risk business activities as well as address privacy, compliance, AI and data governance considerations, including by conducting privacy and AI impact assessments and providing recommendations for risk mitigation

  • Actively engage and collaborate with cross-functional stakeholders to develop and implement technology solutions and ensure adherence to the TELUS' Trust Model

  • Lead the development, design, and implementation of processes, frameworks, technology requirements and testing protocols that standardize best practices in data governance and risk management, and support an agile development methodology

  • Identify, quantify, and escalate data risks promptly, with a sense of urgency, and recommend mitigating controls that are effective to protect the data of our customers and team members

  • Adapt to meet the changing needs of the organization, and a fast-paced ambitious team, where priorities shift but the focus on the mission is steadfast

Qualifications

What you bring

  • Demonstrated ability to enable emerging technologies by building and operationalizing programs related to privacy and AI laws, data ethics, artificial intelligence, data governance and data protection in a responsible and ethical manner

  • Valued for your knowledge and expertise in applying privacy, or other regulatory laws, guidance and best practices, and an understanding of data ethics, artificial intelligence, operational data governance and data protection

  • Trusted as a collaborative partner who will act with integrity and apply critical thinking to fulfil TELUS' commitments to its customers and team members

  • Demonstrated track record of defining and delivering measurable outcomes and risk mitigation for customers and the business in a complex stakeholder environment

  • Known for your ability to be a skilled influencer and negotiator and a persuasive advocate with strong conflict resolution skills that focus on win-win solutions to help develop communities of practice

  • Comfortable with ambiguity and recognized for your ability to make decisions in a fluid environment

  • Ability to effectively and respectfully communicate complex concepts to non-experts

  • Minimum 5 years of industry experience in data ethics, artificial intelligence, operational data governance, privacy and/or data protection

  • Certified International Association of Privacy Professional (IAPP) or willingness and ability to become certified within 6 months

Great-to-haves

  • Bilingualism in English and French, verbal and/or written

  • Legal background/experience

  • Experience working in a large, matrixed organization

Advanced knowledge of English is required because you will most of the time interact in English with external parties (clients, suppliers, candidates, external partners, etc.); interact in English with internal parties (colleagues, internal partners, stakeholders, etc.); and work with IT tools whose interface is only accessible in English as part of this position's main responsibilities given its national scope.

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What TELUS employees say

Pay

Hours and flexibility

Workplace

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