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Labeling Annotation Specialist

Remote: 
Full Remote
Contract: 
Experience: 
Mid-level (2-5 years)
Work from: 
Minnesota (USA), United States

Offer summary

Qualifications:

2-3 years as a labeling specialist/annotator, Experience with text labeling projects in English, Training in Computer Science or related field, Experience with labeling platforms like Labelbox.

Key responsabilities:

  • Annotate and analyze labeling projects
  • Collaborate with AI/ML Team and Product Managers
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Datasite Large https://www.datasite.com/
1001 - 5000 Employees
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Job description

Datasite is where deals are made. We provide the data rooms and SaaS technology used in M&A and other high-value transactions, to deliver projects in more than 170 countries. Carrying that success into the future is all about you. Your useful skills, your unusual experience, your unique ideas. Everyone here brings something unexpected. What’s yours? Invest your talents in us, and we’ll return the compliment.

Job Description:

We are looking for Labeling Annotation Specialists who has experience in all the various labeling steps. They must be willing to learn with us are we build a labeling team that is able to keep up with Data Science requests along with keeping up with and implementing best labeling practices.

At Datasite we are transforming the way companies do Mergers and Acquisitions (M&A). We have the industry leading M&A platform built on a modern micro-services architecture. We are looking for a talented Labeling Annotation Specialist to join our team. As a Labeling Annotation Specialist, you will help provide structure to our Data Science team in procuring good training datasets for our Data Science team to implement and deliver quality models. You will be a part of building AI Models that the smartest minds in finance will rely upon every day. Your work will be highly visible to the executive team and will inform the strategic direction of the company.

This is a remote opportunity within the US with a preference in MN. Please note, we are unable to sponsor or take over sponsorship of an employment Visa at this time.

In this role, you will:

  • Apply industry-leading standards to AI solutions tailored to our sophisticated, high-stakes customer base.
  • Collaborate closely with members of the AI/ML Team, Product Managers and Labeling team to deliver impactful customer solutions.
  • Essential Duties and Responsibilities:
  • Annotate and provide analysis of data labeling projects
  • Create meaningful labeling instructions that could be used internally or externally
  • Receive Data Science requests and convert them into labeling projects; creating a viable timeline with milestones
  • Meet daily, weekly and monthly labeling annotation goals
  • Audit various projects and provide useful and meaningful feedback internal and external workforce

Qualifications:

  • 2-3 years hands on experience as a labeling specialist/Annotato)
  • 2-3 years completing various text labeling projects (doc classification, NER, NLP) in English
  • Training in Computer Science, Machine Learning, AI, Statistics, or related field.
  • Experience working in various labeling platforms (Labelbox, Appen, etc)
  • Natural inclination to seek understanding of customers and consider business context

 Additional Requirements:

  • Ability to work both independently and in conjunction with teams and product groups.
  • Ability to work on multiple projects simultaneously.
  • Ability to interact with internal/external clients/customers in a professional manner.
  • Ability to rapidly acquire new domain knowledge.

As a global organization, Datasite knows that diverse perspectives are essential to our success. We’re committed to maintaining a diverse workforce to serve our customers around the world. Datasite is an equal opportunity employer (EEO) and furthers the principles of EEO through Affirmative Action.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Professional Communication
  • Collaboration

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