Data Annotator - Finance / Accounting
Toronto
Full Time Contract Mid-level / Intermediate USD 60K+
- Remote-first
- Website
- @CohereAI 𝕏
- GitHub
- Search
Cohere
Cohere provides industry-leading large language models (LLMs) and RAG capabilities tailored to meet the needs of enterprise use cases that solve real-world problems.
Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.
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. We like to work hard and move fast to do what’s best for our customers.
Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is the one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
Join us on our mission and shape the future!
Why this role?We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans - by way of feedback. By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech.
This role will have you focus on financial modelling and finance-based questions. You will teach the Cohere model how to perform across a variety of different functions and logic.
Please Note: This is a part-time contract position. We are looking for candidates who are able to commit to 20 hours per week at a $30/hour contract rate (commensurate with experience). This role is BYOD 💻 - Bring Your Own Device (laptop). Once training is completed, this role is hybrid. Performance incentives included!
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.
Our Perks:🤝 An open and inclusive culture and work environment 🧑💻 Work with cutting-edge AI technology 🪴 A vibrant & central location 🥨 A great selection of office snacks 🏆 Performance-based incentives
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. We like to work hard and move fast to do what’s best for our customers.
Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is the one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.
Join us on our mission and shape the future!
Why this role?We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans - by way of feedback. By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech.
This role will have you focus on financial modelling and finance-based questions. You will teach the Cohere model how to perform across a variety of different functions and logic.
Please Note: This is a part-time contract position. We are looking for candidates who are able to commit to 20 hours per week at a $30/hour contract rate (commensurate with experience). This role is BYOD 💻 - Bring Your Own Device (laptop). Once training is completed, this role is hybrid. Performance incentives included!
As a Senior Data Quality Specialist, you will:
- Evaluate the model’s ability to respond to objective financial queries ( you will not be giving financial advice)
- Write financial prompts along with verified information to evaluate the accuracy of the model’s responses
- Label, proofread, and improve machine-written and human-written financial outputs.
- Follow our style guide, and make recommendations on unique situations that fall outside of its scope.
You may be a good fit if you have:
- 2+ years of industry experience working in the finance sector
- Experience with preparing and understanding financial statements, key metrics, business acumen
- Experience with risk analysis processes
- Experience with financial modelling/analysis that informs strategic decision making
- You are an expert in Excel and/or VBA
The Candidate Journey:
- Initial Screening - Once you have submitted your application our Talent Team will review your resume and writing samples.
- Virtual Meet & Greet - If selected to move forward, you will have a short video call with a member of our Annotation Army!
- Practical Assessment - This assignment will test your written skill through various language-based tasks, such as a a writing sample, interacting with a chat bot, and more.
- Offer - Independent Contractor Agreement.
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.
Our Perks:🤝 An open and inclusive culture and work environment 🧑💻 Work with cutting-edge AI technology 🪴 A vibrant & central location 🥨 A great selection of office snacks 🏆 Performance-based incentives
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Tags: Chatbots CoHere Data quality Excel Finance LLMs RAG
Region:
North America
Country:
Canada
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