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Online Data Labelling Jobs in Chicago, IL (NOW HIRING)

Data Scientist II

Chicago, IL · On-site

$138 - $172/hr

Build measurement and evaluation frameworks -- both offline and online -- to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Data Scientist II

Chicago, IL · On-site +1

$130K - $150K/yr

Build measurement and evaluation frameworks -- both offline and online -- to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Build measurement and evaluation frameworks - both offline and online - to assess where and why ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Lead AI Engineer, Data Solutions

Chicago, IL · On-site +1

$118K - $141K/yr

Transform raw interaction data into features, labels, and evaluation datasets * Enable continuous ... Build offline and online evaluation frameworks * Develop evaluation datasets, golden traces, and ...

Cyber Data Protection Manager

Chicago, IL · Remote

$114K - $154K/yr

DLP, sensitivity labels, data classification, DSPM, DSPM for AI, on-demand classification, or ... online communications and digital products, protecting users, consumers, and patients from harm.

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For on-line sales, assist with the data collection of sales promotions and marketing activities, on ... Interface and coordinate with overseas and domestic vendors (designer and printers) any label ...

Handle M365 compliance: retention, sensitivity labels, data governance. Automate admin tasks via ... Online, OneDrive, Teams, and Power Platform. Configure and support M365 groups, licenses, roles ...

... meta-data, content classification, controlled vocabularies, and content tagging Created any ... The art and science of organizing and labeling web sites, intranets, online communities, and ...

Sr Lead, Cybersecurity Engineering

Chicago, IL · On-site

$118K - $161K/yr

... Protection labeling, DLP, Endpoint DLP, Insider Risk, Communication Compliance, Data Lifecycle ... Preferred : • Experience with M365 services (SharePoint Online, Teams, Exchange, Entra ID ...

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This role is responsible for accurately processing prescription data, assisting with medication ... Sort, count, fill, label, pack, and prepare prescription medications for shipment * Operate ...

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Showing results 1-20

Online Data Labelling information

See Chicago, IL salary details

$47.4K

$170K

$250.8K

How much do online data labelling jobs pay per year?

As of Aug 11, 2026, the average yearly pay for online data labelling in Chicago, IL is $169,993.00, according to ZipRecruiter salary data. Most workers in this role earn between $137,500.00 and $175,100.00 per year, depending on experience, location, and employer.

What is the difference between Online Data Labelling vs Data Annotation?

AspectOnline Data LabellingData Annotation
CredentialsBasic computer skills, attention to detailSimilar, often no formal certification required
Work EnvironmentRemote, flexibleRemote or in-office, depending on project
Industry UsageCommon in AI/ML data preparationUsed across AI, computer vision, NLP projects
Search IntentOnline Data Labelling vs Data Annotation

Online Data Labelling and Data Annotation are closely related roles in AI data preparation. While both involve labeling data for machine learning, Online Data Labelling often emphasizes quick, online tasks, whereas Data Annotation may include more detailed, specialized labeling. Both roles are essential in training AI models and share similar skills and work environments.

What is online data labelling?

Online data labelling is the process of tagging or annotating data—such as images, text, or audio—using digital tools to make it understandable for machine learning algorithms. Data labelers review raw data and apply predefined labels to help train artificial intelligence systems, enabling them to recognize patterns and make predictions. This work is essential for improving the accuracy and performance of AI models in various applications, such as image recognition, natural language processing, and autonomous vehicles. Online data labelling jobs are often remote and require attention to detail, consistency, and sometimes domain-specific knowledge.

What are some common challenges faced by online data labellers, and how can they be managed effectively?

Online data labelers often encounter challenges such as repetitive tasks, strict accuracy requirements, and tight deadlines. Maintaining high attention to detail is crucial, as even small errors can impact the quality of machine learning models. To manage these challenges, it's helpful to take regular breaks, use productivity tools, and communicate any ambiguities or unclear instructions with supervisors or team leads. Many organizations also offer support channels and quality assurance feedback to help labelers continuously improve their work.

What are the key skills and qualifications needed to thrive as an online data labeller?

To excel as an Online Data Labeller, you need strong attention to detail, basic data handling skills, and familiarity with data annotation protocols, often requiring at least a high school diploma. Proficiency with data labelling platforms such as Labelbox, Supervisely, or Scale AI, and sometimes knowledge of spreadsheet tools, is typically necessary. Reliability, consistency, and the ability to follow detailed guidelines make individuals stand out in this role. These skills ensure high-quality, accurately labelled datasets that are critical for training effective AI and machine learning models.
What are the most commonly searched types of Data Labelling jobs in Chicago, IL? The most popular types of Data Labelling jobs in Chicago, IL are:
Infographic showing various Online Data Labelling job openings in Chicago, IL as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $169,993 per year, or $81.7 per hour.

Data Scientist II

Arrive Logistics

Chicago, IL • On-site

$138 - $172/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 20 days ago


Arrive Logistics rating

5.5

Company rating: 5.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

Who We Want

The Data Scientist II will work closely with Data Science, Product, and Engineering to build and improve ML and AI systems that drive operational value. This role is a great fit for a hands‑on practitioner with applied experience in NLP and LLM‑based systems who is ready to take on meaningful technical ownership. You’ll contribute to the full lifecycle of production ML systems — from evaluation and measurement through development, deployment, and iteration — with a particular focus on text and language‑based applications. The ideal candidate is comfortable operating in ambiguous problem spaces, can translate loosely defined business needs into concrete technical approaches, and communicates findings clearly to both technical and non‑technical audiences.

What You’ll Do
  • Develop, evaluate, and iterate on NLP and LLM‑based systems, including text classification, information extraction, and context retrieval pipelines.
  • Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements.
  • Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality.
  • Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine‑tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data.
  • Perform structured analysis of system performance to surface failure modes, data gaps, and high‑value areas for investment, applying sound statistical reasoning to evaluation results.
  • Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production.
  • Contribute to standards and best practices around deploying, evaluating, and monitoring text and language‑based ML systems.
  • Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time.
  • Collaborate with senior data scientists and cross‑functional partners to translate business needs into well‑scoped technical solutions, including communicating findings and recommendations to non‑technical stakeholders.
Qualifications
  • Bachelor’s or Master’s degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience.
  • Hands‑on experience building or improving NLP or LLM‑based systems in applied settings.
  • Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail.
  • Experience with both prompt engineering and fine‑tuning approaches for language tasks, with the judgment to know when to apply each.
  • Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance.
  • Experience with Hugging Face Transformers for text classification or related NLP tasks.
  • Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance.
  • Proficiency in Python and SQL, and comfort working with structured and unstructured data.
  • Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined.
  • Strong written communication skills; able to document systems and findings clearly and present recommendations to non‑technical stakeholders.
  • Experience designing data annotation workflows, labeling guidelines, or label quality processes is a plus.
  • Experience with model deployment, monitoring, or production ML workflows is a plus.
  • Familiarity with LangChain and LangSmith or similar LLM orchestration and observability tooling is a plus.
  • Transportation or logistics industry experience is a plus.
The Perks of Working With Us
  • Take advantage of our comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage.
  • Invest in your future with our matching 401(k) program.
  • Build relationships and take part in learning opportunities through our Employee Resource Groups.
  • Enjoy office wide engagement activities, team events, happy hours and more!
  • Leave the suit and tie at home; our dress code is casual.
  • Work in the heart of downtown Chicago, IL!
  • Sweat it out at the LifeStart gym in our office building that includes brand new Peloton bikes, top‑of‑the‑line equipment and personal training options.
  • Maximize your wellness with free counseling sessions through our Employee Assistance Program
  • Take time to manage your physical and mental health – we offer company paid holidays, paid vacation time and wellness days.
  • Receive 100% paid parental leave when you become a new parent.
  • Get paid to work with your friends through our Referral Program!
  • Get relocation assistance! If you are not local to the area, we offer relocation packages.

$138,000 – $172,000 a year

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