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Commission Medical Data Annotation Jobs in Arizona

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130.50K - $177.30K/yr

Experience with data annotation tools and platforms for manual or semi-automated labeling ... This includes a variety of medical, dental and vision plan offerings you can choose from that best ...

Senior Data Engineer / Data Curator

Phoenix, AZ · On-site

$130.50K - $177.30K/yr

Experience with data annotation tools and platforms for manual or semi-automated labeling ... This includes a variety of medical, dental and vision plan offerings you can choose from that best ...

We offer comprehensive benefits including medical/dental/vision insurance, HSA, FSA, 401(k), and ... This job is not eligible for bonuses, incentives or commissions. Kforce is an Equal Opportunity ...

New

Medical - Medical Assistant

Tucson, AZ · On-site

$17.48 - $23.38/hr

Successful completion of a Medical Assistant program accredited by CAAHEP (Commission on ... Documents immunization data in the patients' charts and in the Arizona State Immunization ...

Medical Coder

Tucson, AZ

$18 - $24/hr

Abstracts and enters all data for coding, billing, GPRA indicators and CMS, The Joint Commission ... Identifies inconsistencies within the medical record and participates in QA functions and peer ...

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Showing results 1-20

Commission Medical Data Annotation information

What are the key skills and qualifications needed to thrive as a Commission Medical Data Annotation Specialist, and why are they important?

To thrive as a Commission Medical Data Annotation Specialist, you need a solid understanding of medical terminology, data annotation techniques, and attention to detail, often with a background in life sciences or healthcare. Familiarity with annotation platforms, data labeling tools, and compliance standards such as HIPAA is typically required. Strong analytical skills, meticulousness, and effective communication make someone stand out in this position. These skills are crucial for ensuring high-quality, accurate data that supports reliable AI and research outcomes in medical applications.

What are some common challenges faced in a Commission Medical Data Annotation role and how can they be addressed?

In a Commission Medical Data Annotation role, professionals often encounter challenges such as interpreting complex medical terminology, ensuring consistency in labeling, and maintaining high accuracy under tight deadlines. To address these, it is helpful to regularly reference standardized guidelines, participate in team reviews or audits, and seek clarification from medical experts when needed. Collaborating with peers and utilizing annotation tools efficiently can also help streamline the process and minimize errors, ensuring both quality and productivity.

What are commission medical data annotation jobs?

Commission medical data annotation jobs involve labeling and categorizing medical data—such as images, clinical notes, or audio recordings—for use in training machine learning models in healthcare. Workers are typically paid based on the amount of data they accurately annotate, rather than an hourly wage. Tasks may include identifying diseases in medical images, transcribing doctor notes, or classifying medical records. These jobs are critical for developing reliable artificial intelligence systems in medicine, supporting applications like diagnostics, treatment planning, and research. Attention to detail, understanding of medical terminology, and adherence to privacy standards are essential in these roles.

What is the difference between Commission Medical Data Annotation vs Medical Data Labeler?

AspectCommission Medical Data AnnotationMedical Data Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or office-based, tech-focusedRemote or office-based, tech-focused
Industry UsageUsed in AI training for healthcare applicationsUsed in AI training for healthcare applications
Search IntentComparison of roles in medical data annotationComparison of roles in medical data annotation

Both roles involve labeling medical data to train AI systems, often requiring similar skills and work environments. The main difference lies in the scope: Commission Medical Data Annotation may involve more specialized tasks or higher-level responsibilities, whereas Medical Data Labeler typically refers to the basic task of data labeling. Understanding these distinctions helps job seekers identify roles aligned with their skills and career goals.

What are the most commonly searched types of Medical Data Annotation jobs in Arizona? The most popular types of Medical Data Annotation jobs in Arizona are:
What are popular job titles related to Commission Medical Data Annotation jobs in Arizona? For Commission Medical Data Annotation jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Commission Medical Data Annotation jobs in Arizona look for? The top searched job categories for Commission Medical Data Annotation jobs in Arizona are:
What cities in Arizona are hiring for Commission Medical Data Annotation jobs? Cities in Arizona with the most Commission Medical Data Annotation job openings:

Senior Data Engineer / Data Curator

TSMC

Phoenix, AZ • On-site

$130.50K - $177.30K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


TSMC rating

8.2

Company rating: 8.2 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

35th of 137 rated electronics manufacturers


Job description

Senior Data Engineer / Data Curator

A job at TSMC Arizona offers an opportunity to work at the most advanced semiconductor fab in the United States. TSMC Arizona's first fab will operate it's leading-edge semiconductor process technology (N4 process), starting production in the first half of 2025. The second fab will utilize its leading edge N3 and N2 process technology and be operational in 2028. The recently announced third fab will manufacture chips using 2nm or even more advanced process technology, with production starting by the end of the decade. America's leading technology companies are ready to rely on TSMC Arizona for the next generations of chips that will power the digital future.

As a Senior Data Engineer in the AI Data Curation track, you will ensure that the data powering our AI models is high-quality, well-organized, and fit for use in model training and deployment. You will play a key role in designing and maintaining scalable data pipelines, ensuring that data is clean, relevant, and aligned with ethical and compliance standards.

Responsibilities:

  • Design and implement data pipelines for processing, cleaning, and curating large datasets used in model training and fine-tuning.
  • Automate data cleaning processes (e.g., removing noise, duplicates, irrelevant content) and ensure datasets are appropriately labeled and structured.
  • Collaborate with model teams to ensure data aligns with model requirements and performance goals.
  • Assess and mitigate bias in datasets, ensuring that models are trained on diverse and representative data.
  • Manage data storage and retrieval strategies, ensuring scalability and data consistency across different environments.
  • Conduct regular audits to ensure data integrity, privacy, and security compliance.

Minimum Qualifications/Requirements:

Education: Minimum degree required: Bachelor's degree in Computer Science, Data Science, or a related field.

Technical Skills:

  • 5+ years of experience in data engineering, data wrangling, or data curation, particularly in machine learning or AI-driven environments.
  • Strong proficiency in Python (Pandas, NumPy) and SQL for data manipulation and querying.
  • Familiarity with cloud-based data storage (AWS S3, Google Cloud Storage, etc.) and distributed systems for managing large datasets.
  • Experience with data annotation tools and platforms for manual or semi-automated labeling.
  • Experience with NLP data formats, such as JSONL, text, or embeddings, and an understanding of tokenization.
  • Experience managing data pipelines with tools like Apache Kafka, Apache Airflow, or similar ETL tools.
  • Strong knowledge of AI ethics, data privacy, and compliance standards (GDPR, CCPA, etc.).
  • Bonus: Experience with vector databases and indexing for LLMs (e.g., FAISS, Pinecone).

Interpersonal Skills:

  • Communication
  • Computer proficiency
  • Presentation skills
  • Listening
  • Teamwork

Candidates must be willing and able to work on-site at our Phoenix Arizona facility.

As a valued member of the TSMC family, we place a significant focus on your health and well-being. When you are at your best-physically, mentally, and financially-our company is at its best. We offer a comprehensive and competitive benefits program that provides the resources you need to help you manage your health and achieve your goals across many areas of your life. This includes a variety of medical, dental and vision plan offerings you can choose from that best fit your and your family's needs. Additionally, TSMC provides income-protection programs to financially assist you should you experience an injury or illness, and a 401(k)-retirement savings plan to help you secure your financial future. TSMC also offers competitive paid time-off programs and paid holidays allowing you to recharge and spend time with your family and loved ones.

Work Location: 5088 W. Innovation Circle, Phoenix, AZ 85083

TSMC is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic. We encourage all qualified individuals to apply, and we welcome applications from individuals with diverse backgrounds and experiences. Candidates must be able to perform the essential functions of the job with or without a reasonable accommodation. If you need a reasonable accommodation as part of this application process, please contact P_LOA@tsmc.com.

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