1

Home Based Medical Data Annotation Jobs in Columbus, OH

This is powered by high-quality annotated data and detailed annotation schemes that are the ... Those in eligible roles may receive commission-based pay and/or discretionary incentive ...

Senior AI/ML Engineer

Columbus, OH · On-site +1

$97.60K - $134.10K/yr

This role is based remotely but if you live within a 50-mile radius of Sunnyvale, CA you are ... data-annotation pipelines and machine-led training data solutions at foundation-model scale . We ...

Home Health Aide

Columbus, OH · On-site

$14 - $18/hr

Medical & Prescription Drug Plan * Telehealth * Dental * Vision * 401K * Life Insurance * Short ... based care services to more than 3,000 clients a month carefully coordinated to keep clients ...

Home Health Aide

Logan, OH · On-site

$12.25 - $15.75/hr

Medical & Prescription Drug Plan * Telehealth * Dental * Vision * 401K * Life Insurance * Short ... based care services to more than 3,000 clients a month carefully coordinated to keep clients ...

Home Health Aide

Lancaster, OH · On-site

$13.25 - $17/hr

Medical & Prescription Drug Plan * Telehealth * Dental * Vision * 401K * Life Insurance * Short ... based care services to more than 3,000 clients a month carefully coordinated to keep clients ...

next page

Showing results 1-20

Home Based Medical Data Annotation information

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

To thrive as a Home Based Medical Data Annotation Specialist, you need a solid understanding of medical terminology, attention to detail, and experience with data labeling—often supported by a background in healthcare or life sciences. Familiarity with annotation platforms, EHR systems, and relevant data security protocols is typically required, and some employers may prefer certifications in medical coding or data management. Strong organizational skills, self-motivation, and effective written communication help individuals excel in remote, deadline-driven environments. These competencies ensure accurate, high-quality data labeling that is essential for developing reliable AI systems in healthcare.

What are some common challenges faced by professionals working in home-based medical data annotation, and how can they be managed?

One common challenge in home-based medical data annotation is maintaining accuracy and consistency when labeling complex medical images or records, as errors can impact critical healthcare outcomes. Working remotely may also lead to feelings of isolation or difficulty staying updated with annotation guidelines. To manage these challenges, it's important to establish a quiet, dedicated workspace, participate in regular virtual team meetings, and utilize provided training resources. Staying engaged with peers through communication channels and seeking feedback from supervisors can also help ensure high-quality work and ongoing professional development.

What is home based medical data annotation?

Home based medical data annotation involves labeling and categorizing medical data, such as images, audio, or text, from the comfort of your home. Annotators help train artificial intelligence (AI) systems by identifying and marking relevant information, such as highlighting tumors in X-rays or transcribing medical notes. This role is essential for improving the accuracy and efficiency of AI tools used in healthcare diagnostics, research, and patient care. Typically, it requires attention to detail, a basic understanding of medical terminology, and familiarity with annotation tools.

What is the difference between Home Based Medical Data Annotation vs Home Based Medical Transcription?

AspectHome Based Medical Data AnnotationHome Based Medical Transcription
Required CredentialsBasic medical knowledge, attention to detailMedical terminology, transcription skills, sometimes certification
Work EnvironmentRemote, computer-basedRemote, computer-based
Industry UsageAI training, data labeling for healthcare AI modelsConverting audio to written reports for medical records
Common Search/ComparisonYesYes

Home Based Medical Data Annotation involves labeling medical images and data to train AI systems, requiring attention to detail and basic medical knowledge. In contrast, Home Based Medical Transcription focuses on converting audio recordings into written medical reports, often needing transcription skills and familiarity with medical terminology. Both roles are remote and industry-specific, but they serve different purposes within healthcare technology and documentation.

What are the most commonly searched types of Medical Data Annotation jobs in Columbus, OH? The most popular types of Medical Data Annotation jobs in Columbus, OH are:
What are popular job titles related to Home Based Medical Data Annotation jobs in Columbus, OH? For Home Based Medical Data Annotation jobs in Columbus, OH, the most frequently searched job titles are:
What job categories do people searching Home Based Medical Data Annotation jobs in Columbus, OH look for? The top searched job categories for Home Based Medical Data Annotation jobs in Columbus, OH are:
What cities near Columbus, OH are hiring for Home Based Medical Data Annotation jobs? Cities near Columbus, OH with the most Home Based Medical Data Annotation job openings:
Data Domain Architect Lead

Data Domain Architect Lead

Chase

Columbus, OH • On-site

Other

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


JPMorgan Chase & Co. rating

8.1

Company rating: 8.1 out of 10

Based on 466 frontline employees who took The Breakroom Quiz

46th of 141 rated banks


Job description

Data Domain Architect Lead

Machine Learning and Artificial Intelligence play a critical role in transforming Consumer and Community Banking Operations. The ability to utilize data in meaningful ways allows us to develop solutions which both our customers and employees can benefit from. Customers expect tailored servicing and Chase is looking to deliver personalization to meet their needs. This is powered by high-quality annotated data and detailed annotation schemes that are the backbone of impactful Artificial Intelligence/Machine Learning (AI/ML) algorithms and applications.

As a Data Domain Architect Lead within the Data Annotation team, you will use your domain expertise and people-leading experience to partner your team closely with teams in Data Science, Analytics, and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other linguistic resources to help train machine learning models, drive insight, analysis, and possible content creation.

Job Responsibilities

  • Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
  • Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
  • Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
  • Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
  • Actively contribute to the team's continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group

Required Qualifications, Capabilities, and Skills

  • 6+ years of related experience in development of machine learning solutions
  • Familiar with industry annotation and labeling methods
  • Experience with various data modeling techniques and tools
  • Familiar with Finance and Banking products
  • Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
  • Excellent analytical and problem-solving skills and the ability to pay close attention to detail
  • Experience using Python in working with and analyzing large real-world datasets
  • Working knowledge of information and data retrieval
  • Working knowledge of machine learning and artificial intelligence paradigms and libraries
  • Familiar with Large Language Models (LLMs) and prompt engineering

Preferred Qualifications, Capabilities, and Skills

  • Masters or PhD in a related field, or Bachelors
  • Technical understanding of common relational database systems; i.e., Teradata and Oracle
  • Excellent command of the Structured Query Language (SQL)
  • Knowledge of SAS or Scala, and Python languages
  • Knowledge of Advanced Statistics
  • Advanced analytical thinking and problem-solving skills
  • Strong interpersonal & communication skills

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction. The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.


What JPMorgan Chase & Co. employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom