1

Freelance Machine Learning Data Annotation Jobs in Vancouver, BC

Title and Summary Data Scientist II Overview The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard ...

Title and Summary Director, Data Science Overview The Security Solutions Data Science team is responsible for delivering Artificial Intelligence (AI) and Machine Learning (ML) models that support ...

... machine learning. Traditional approaches to small molecule drug discovery require over ten years ... We are searching for a chemical data scientist / cheminformatician to join us in our quest to ...

We are currently seeking a Manager, Machine Learning Engineering to join our rapidly growing ... Collaborate cross-functionally with MLOps engineering, product management, operations, and data ...

Data Scientist III

Vancouver, BC · Hybrid

CA$107K - CA$132K/yr

Design, develop, and deploy machine learning models, advanced analytics, and Generative AI ... Master's or PhD in Data Science, Computer Science, Statistics, or a related quantitative field ...

Data Scientist II

Burnaby, BC · On-site

CA$128K - CA$144K/yr

The Trust Machine Learning team protects Remitly's customers by developing intelligent systems that prevent fraud. These systems assess the risk of every transaction and customer interaction, while ...

You will lead the architecture and evolution of critical data systems spanning ingestion, warehousing, machine learning feature generation, identity resolution, and activation at massive scale. As a ...

You will lead the architecture and evolution of critical data systems spanning ingestion, warehousing, machine learning feature generation, identity resolution, and activation at massive scale. As a ...

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and ...

Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and ...

You'll transform raw, unstructured data into clean, reliable datasets that power machine learning applications. Working alongside ML Developers and Researchers, you'll design and implement data ...

Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or equivalent practical experience * 8+ years building cloud-native software in production (distributed systems ...

Senior Data Analyst

Vancouver, BC · On-site

$60 - $70/hr

Our Vancouver client is seeking a Senior Data Analyst to join their team, must be available to work ... Machine Learning: Practical experience implementing ML/AI models in a production environment.

Showing results 41-60

Freelance Machine Learning Data Annotation information

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What are the most commonly searched types of Machine Learning Data Annotation jobs in Vancouver, BC?

The most popular types of Machine Learning Data Annotation jobs in Vancouver, BC are:

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Vancouver, BC?

For Freelance Machine Learning Data Annotation jobs in Vancouver, BC, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Vancouver, BC look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Vancouver, BC are:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Vancouver, BC as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 16% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Full-time

Re-posted 21 hours ago


Job description

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build asustainableeconomy where everyone can prosper. We support a wide range of digital payments choices, making transactionssecure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Data Scientist IIOverview
The Security Solutions Data Science team is responsible for developing Artificial Intelligence (AI) and Machine Learning (ML) models that power Mastercard's Identity and risk solutions across authentication and authorization use cases. These models are production-ready and designed to support key products and capabilities that help make digital transactions safer, smarter, and more trusted.
In addition to building models, the team is responsible for the research and development of scalable end-to-end data science capabilities covering the full lifecycle of model creation-from data extraction and feature engineering to validation, deployment, and monitoring. These capabilities must be designed to scale and to be repeatable, resilient, and industrialized so they can support long-term product growth and evolving business needs.
Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. Within this space, the Identity Data Science portfolio plays an important role in advancing intelligence-driven solutions that enable more effective risk assessment and decisioning across the merchant lifecycle.
You will join a dynamic and innovative team working at scale with modern big data platforms and technologies. In this role, you will focus on solving merchant risk during onboarding and ongoing monitoring through the research and development of a merchant registry and profiling capability within the Identity Data Science portfolio. This includes helping build the foundational data assets, profiling logic, analytical workflows, and machine learning approaches needed to better understand merchant behavior, relationships, and risk signals over time.
Role
You will contribute to the design and development of data science capabilities that improve merchant risk assessment across onboarding and monitoring workflows.
Key responsibilities include:
Analyze large-scale transaction, merchant, and related entity data to identify patterns, trends, and anomalies
Support the research and development of a merchant registry and profiling capability to strengthen merchant risk assessment during onboarding and ongoing monitoring
Contribute to feature engineering, entity resolution, and analytical workflows that improve merchant-level intelligence
Prototype machine learning and analytical solutions under guidance from senior team members
Help build and maintain scalable data and model workflows using Databricks and Spark-based environments
Identify appropriate techniques for different analytical problems and help validate solutions through structured testing, benchmarking, and performance evaluation
Support model monitoring, benchmarking, and iterative improvement of data science solutions
Work closely with partners across Data Science, Product, and Engineering in an Agile environment to support iterative delivery and continuous improvement
All About You
Essential Skills to be successful:
Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or another quantitative discipline such as Engineering, Economics, or Physics
Experience in applying data science and machine learning to solve real business problems
Solid foundation in statistics, analytics, and core machine learning concepts
Experience with Python and SQL; familiarity with tools such as Pandas for data manipulation and analysis
Exposure to large datasets and interest in scalable data processing; familiarity with Spark is a plus
Experience with writing clean, modular, and well-documented code following Data Science best practices. Ability to collaborate effectively through code contributions, peer reviews, and shared development workflows to ensure robust, maintainable, and efficient solutions
Ability to identify appropriate analytical techniques and validate solutions through structured evaluation
Critical thinking and a drive to produce high quality work, ensuring that all solutions meet rigorous standards
Understanding of Agile methodologies, with the ability to contribute to iterative delivery
Openness to learn and apply new technologies, staying current with industry trends and advancements
Good communication skills, enabling effective collaboration with team members and stakeholders
Self-driven with a collaborative mindset and enthusiasm for learning in a fast-paced, innovative environmentMastercard is a merit-based, inclusive, equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. We hire the most qualified candidate for the role. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly.

Corporate Security Responsibility


All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

  • Abide by Mastercard's security policies and practices;

  • Ensure the confidentiality and integrity of the information being accessed;

  • Report any suspected information security violation or breach, and

  • Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

In line with Mastercard's total compensation philosophy and assuming that the job will be performed in Canada, the successful candidate will be offered a competitive pay based on location, experience and other qualifications for the role and may be eligible to participate in a discretionary annual incentive program.

Pay Ranges

Vancouver, Canada: $91,000 - $140,000 CAD