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Medical Data Annotation Jobs in Chicago, IL (NOW HIRING)

Experience designing data annotation workflows, labeling guidelines, or label quality processes is ... Take advantage of our comprehensive benefits package, including medical, dental, vision, life ...

Data Scientist II

Chicago, IL · On-site +1

$130K - $150K/yr

Experience designing data annotation workflows, labeling guidelines, or label quality processes is ... Take advantage of our comprehensive benefits package, including medical, dental, vision, life ...

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets ... • Medical, Dental, and Vision Insurance • Free Breakfast, Lunch, and Dinner (where applicable ...

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Medical Data Annotation information

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$10

$22

$53

How much do medical data annotation jobs pay per hour?

As of Jul 26, 2026, the average hourly pay for medical data annotation in Chicago, IL is $22.91, according to ZipRecruiter salary data. Most workers in this role earn between $15.30 and $23.44 per hour, depending on experience, location, and employer.

What is a Medical Data Annotation job?

A Medical Data Annotation job involves labeling and categorizing medical data, such as patient records, medical images, and clinical notes, to help train artificial intelligence (AI) models. Annotators ensure that AI systems can accurately interpret medical information by applying domain-specific knowledge and following strict guidelines. This role requires attention to detail, familiarity with medical terminology, and sometimes collaboration with healthcare professionals to ensure accuracy.

What are the key skills and qualifications needed to thrive in the Medical Data Annotation position, and why are they important?

To thrive in Medical Data Annotation, you need a solid understanding of medical terminology, attention to detail, and familiarity with clinical or healthcare data formats, often backed by relevant coursework or experience in healthcare or life sciences. Proficiency with data annotation platforms, medical coding software, and sometimes certifications like HIPAA compliance are highly valued. Strong communication skills, a high level of accuracy, and the ability to work both independently and collaboratively set standout candidates apart. These skills help ensure data integrity and support the development of reliable AI-powered healthcare solutions.

What are the typical challenges faced in Medical Data Annotation roles?

One of the main challenges in Medical Data Annotation is accurately interpreting complex medical information and ensuring consistency across large datasets. Annotators often work with sensitive patient data, so maintaining confidentiality and adhering to strict data security protocols is essential. The work can be repetitive and detail-oriented, but it is crucial for training reliable medical AI systems. Successful Medical Data Annotation professionals stay motivated by understanding the impact of their work on advancing medical research and patient care.

What are the most commonly searched types of Medical Data Annotation jobs in Chicago, IL? The most popular types of Medical Data Annotation jobs in Chicago, IL are:
What are popular job titles related to Medical Data Annotation jobs in Chicago, IL? For Medical Data Annotation jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Medical Data Annotation jobs in Chicago, IL look for? The top searched job categories for Medical Data Annotation jobs in Chicago, IL are:
Infographic showing various Medical Data Annotation job openings in Chicago, IL as of July 2026, with employment types broken down into 2% Locum Tenens, 35% Full Time, 26% Part Time, 1% Contract, 35% Nights, and 1% Summer. Highlights an 55% Physical, 2% Hybrid, and 43% Remote job distribution, with an average salary of $47,649 per year, or $22.9 per hour.
Data Scientist II

Data Scientist II

Arrive Logistics

Chicago, IL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 4 days ago


Arrive Logistics rating

4.3

Company rating: 4.3 out of 10

Based on 8 frontline employees who took The Breakroom Quiz


Job description

Who We Are
Arrive Logistics is a leading transportation and technology company in North America with plans to grow significantly year over year. Our success is a testament to our remarkable team and what we're building together. We're committed to providing employees with a meaningful work experience and have established an award-winning culture that supports personal and career development in a fun, casual, and collaborative environment.
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.

$130,000 - $150,000 a year
The base salary range for this position is $130K - $150K, plus bonus and benefits. The range displayed on each job posting reflects the pay range for the position across all locations. Within the range, individual pay is determined based on work location, job-related skills, experience, relevant education or training.
Your Arrive Experience
When we say "award-winning culture," we mean it. We've been recognized as a top workplace by Inc. Fast Company, Fortune, and earned Top Workplaces and Great Place to Work, to name a few. We intend on topping many more of those lists in the years to come, but we're not in it for the trophies. We're committed to culture because it keeps us connected to each other and invested in our shared success while having a blast along the way. Our employee-founded resource groups create communities within Arrive's walls, including Women in Logistics, Emerging Professionals, Prisms, Black Logistics Group, Salute and Unidos.
Notice:
To ensure a safe and transparent interview process, we want to note that Arrive Logistics adheres to strict recruitment practices. Candidates undergo an interview process, and Arrive Logistics does not provide unsolicited job offers. If you have concerns about receiving a fraudulent offer, please contact [email protected] for verification.

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