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Hiring now · posted 117d ago Law Contract · Remote

Data Annotation Specialist, Data Science

at Cohere

Pay not published

The rate is shared during the application.

Remote · Canada Language: English Posted 3 Jul 2026

About this role

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Who are we?

Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.

We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.

We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!

Why this role?

This role will focus on evaluating data science and coding tasks, requiring you to review and debug code, analyze model trajectories, and assess data visualization script development and logical flow implementation. Your work will contribute to our model development efforts and the logic our models apply when completing task requests.

Please note: This is a part-time independent contractor position available within Canada. We seek candidates who are able to commit to 16 hours per week minimum at a 40 CAD/hour contract rate. This role is BYOD 💻 - Bring Your Own Device (laptop). Remote work within Canada. 12 month contract.

As a Data Annotation Specialist, you will:

  • Evaluate the model's ability to respond to coding requests, workflows, and code base-related questions using available tools.

  • Assess agent trajectories and model capabilities for code generation, tabular and graphic manipulation, and debugging requests.

  • Prompt models to complete complex data science tasks and review the accuracy of generated responses.

  • Label, proofread, and improve machine-written and human-written software engineering-related outputs.

  • Report quality and performance trends related to model/agent behaviour and project assignments.

You may be a good fit if you have:

  • Exceptional data analysis and visualization skills.

  • 3+ years of relevant industry experience working on real-world data science problems and pipelines.

  • Proficient knowledge and understanding of Python and industry-standard data science packages (numpy, pandas, matplotlib, sqlite, or others).

  • Strong understanding of SQL syntax writing and workflows; and a deep familiarity with file/data formats, such as markdown, JSON, XML, YAML, and HTML.

  • Prior experience re-writing, proofreading, and delivering feedback on code.

  • Familiarity with code agents (OpenCode, Claude Code, Codex) or evaluating agent trajectories is a plus.

The Candidate Journey:

  • Initial Screening: Our Talent Team will review your application.

  • First Assessment: If selected to move forward, you’ll receive a multiple-choice assessment by email.

  • Second Assessment: Candidates who achieve a passing score will be contacted by a member of our team to complete a more comprehensive assessment focused on their area of expertise.

  • Video Screen: If selected to move forward, you’ll have a short video call with a member of our Operations Team.

  • Final: Selected candidates will receive an Independent Contractor Agreement.

As an independent contractor, you maintain control over how you complete your work and may work with multiple clients simultaneously. We request that you declare any external work relationships with Cohere’s direct competitors and always maintain the IP confidentiality of the Cohere project. Independent contractors are not eligible for health benefits or other benefits provided to employees. Compensation for services is provided to contractors by self-invoicing for services provided pursuant to the terms of our agreement with the contractor.

It is important to understand that, as an independent contractor, continuous work is not guaranteed. The client-contractor relationship is fundamentally project-based, meaning engagements may be temporary, periodic, or intermittent based on our organizational needs and project availability. As an independent contractor, you should anticipate fluctuations in workflow and, therefore, compensation for services when Cohere does not require as many hours of services in a week.

Prospective candidates, please be advised: this role involves working with human-generated and model-generated tasks that may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material.

If the above qualifications do not perfectly align with your experience, we still encourage you to apply!

We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.

This is a remote role. Applicants must be located in: Canada.

How applying works

  1. Click Apply now and enter your email.
  2. You go straight to the application. We email you a copy of this role and your link.
  3. You apply on Cohere's own careers page. Zekai is not the employer and never charges you.
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What to know before you apply

Location
Only applicants located in Canada can be paid for this role. Platforms usually verify where you are, so apply only if you are based there.
Credentials
The listing asks for 3+ years of experience. Put it in the first line of your profile: reviewers screen for it before anything else.
Test tips for data scientists
  • Check data leakage, metric choice and baselines before anything else.
  • Rebuild key numbers in a notebook when you can.
  • Explain trade-offs in plain language; reviewers value clarity.
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