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Data Annotation Research Jobs in Wisconsin (NOW HIRING)

Sr. Data Engineer

Madison, WI · On-site

$115K - $138K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI · On-site

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI

$114K - $137K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Sr. Data Engineer

Madison, WI

$115K - $138K/yr

Enable self-service analytics for R&D and product teams by exposing well- governed, documented data ... control, annotation, genotype imputation, genomic evaluation) using cloud and Databricks ...

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

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

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
What are popular job titles related to Data Annotation Research jobs in Wisconsin? For Data Annotation Research jobs in Wisconsin, the most frequently searched job titles are:
Research Scientist I

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago


Medical College Of Wisconsin rating

7.7

Company rating: 7.7 out of 10

Based on 28 frontline employees who took The Breakroom Quiz

113th of 544 rated colleges and universities


Job description

Summary
The Data Science Institute, in collaboration with the Department of Physiology, at the Medical College of Wisconsin seeks a highly motivated Research Scientist to join a collaborative research team focused on ontology and data curation for diverse research communities. This role supports the Hogan Laboratory in the Data Science Institute and the Rat Genome Database in the Department of Physiology by developing, maintaining, enhancing, and implementing biomedical ontologies in various software, annotation, and data management applications. The incumbent will gain experience in the theory and practice of biomedical, health, and behavioral ontologies, including advanced ontology development workflows. The incumbent will also extract relevant information from published journal articles, research laboratories, and databases and integrate this information with existing data.
A key project is the Advancing Prevention Research in Cancer through Ontology Tools (APRICOT) Project funded by the US National Institutes of Health (NIH), working with behavioral scientists and ontologists across three other European sites. This project is developing ontologies and associated tools and resources to be used in reporting behavior research. This position will work on the development of the Ontology for Modeling and Representation of Social Entities (OMRSE) and its interoperability with the Behaviour Change Intervention Ontology (BCIO).
The position also is an integral team member of the Rat Genome Database (RGD). RGD is the dedicated NIH-funded knowledgebase for the laboratory rat, along with human and several mammalian disease models; RGD curates multiple genomic data types, comprehensive disease and phenotype annotations, and develops novel tools to effectively mine, analyze and visualize the available data. The incumbent will independently conduct data curation including data acquisition, ontology development, and analysis for research projects whose focus is to provide comprehensive disease, clinical and physiological data to diverse research communities. They will work with technical team members on the development of data analytic tools and pipelines, as well as provide input into database and user interface design.
Primary Responsibilities
  • Data curation
  • Perform data acquisition and analysis, including identifying relevant sources of information, extracting clinical, disease, physiological and genetic information from text sources such as published literature and clinical records as well as web-based and other sources.
  • Develop content for web-based research resources.
  • Work with programmers and other curators to develop new and update existing data analysis tools, database design, and web interfaces.
  • Ontology development and implementation
  • Contribute to the development of the Ontology for Modeling and Representation of Social Entities (OMRSE); manage the issue tracker; create periodic releases; lead development meetings.
  • APRICOT project deliverables, including but not limited to developing interoperability between OMRSE and the BCIO and the annotation of Social Determinants of Health instruments and data.
  • Participate in APRICOT meetings, events.
  • Contribute to the development of the Rehabilitation Ontology (REHABO); manage the issue tracker; create periodic releases; lead development meetings.
  • Contribute to ontology and vocabulary development for the Rat Genome Database, including but not limited to the Rat Disease Ontology (RDO)
  • Contribute to the development of the Drug Ontology (DrOn); manage the issue tracker; create periodic releases; lead development meetings.
  • General Responsibilities
  • Mentor graduate students and contribute to training and scientific development within the lab
  • Assist with the development of grant proposals and collaborative research initiatives
  • Coordinate research study activities; lead and manage projects including presenting project updates at meetings
  • Assist in creating workshops, presentations, and educational materials
  • May oversee the work of laboratory personnel, including training and development as well as daily work direction/delegation/prioritizing
  • Other duties as assigned

Knowledge - Skills - Abilities
  • Required knowledge: ontology, terminology, controlled vocabularies, data models
  • Technical knowledge: Familiarity with Web Ontology Language, Protégé, GitHub, relational database management systems / SQL, public sequence databases, and model organism databases is highly desired
  • Enthusiastic, highly motivated, and proven ability to work independently, manage time effectively, and troubleshoot experiments
  • Strong interest and aptitude for multi-disciplinary collaboration
  • Skills and abilities: writing skills, presentation skills, organization, time management, multi-tasking.

Qualifications
Minimum Required Education: PhD in Biomedical Informatics, Ontology, Molecular Biology, Physiology, Computer Science, Artificial Intelligence, Biomedical Engineering, Bioinformatics, Biological or Health Sciences or comparable field
Preferred Experience: 5 years of research experience
  • Experience reviewing and interpreting scientific literature and research data.
  • Experience using tools for ontology development, annotation, term matching, referent tracking, semantic web.
  • Expertise using public genomic or disease data resources and software tools, data acquisition, integration or standardization; clinical, laboratory or informatics experience.
  • Work experience with collaborating with domain experts to solicit priorities for ontology development and formulating term definitions and axioms.
  • Strong publication record in peer-reviewed journals.

Appropriate experience may be substituted for education on an equivalent basis. Master's degree plus an additional minimum of 3 years of relevant research experience may be considered in lieu of a PhD.
#LI-FL1
Physical Requirements
Work requires occasionally lifting moderate weight materials, standing, or walking continuously.
Work Environment
Occasional exposure to dust, noise, temperature changes, or contact with water or other liquids. Work is performed in an environmentally controlled environment.
Sensory Acuity
Ability to detect and translate speech or other communication required. May occasionally require the ability to distinguish colors and perceive relative distances between objects.
Why MCW?
  • Outstanding Healthcare Coverage, including but not limited to Health, Vision, and Dental. Along with Flexible Spending options
  • 403B Retirement Package
  • Competitive Vacation and Paid Holidays offered
  • Tuition Reimbursement
  • Paid Parental Leave
  • Employee & Family Assistance Program (EFAP)
  • Pet Insurance
  • On campus Fitness Facility, offering onsite classes
  • Additional discounted rates on items such as: Select cell phone plans, local fitness facilities, Milwaukee recreation and entertainment etc.

For a brief overview of our benefits see: Benefits Overview
For a full list of positions see: MCW Careers
At MCW all of our endeavors, from our internal operations to our interactions with our partners, are driven by our shared organizational values: Caring - Collaborative - Curiosity - Inclusive - Integrity - Respect. We are committed to fostering an inclusive environment that values diversity in backgrounds, experiences, and perspectives through merit-based processes and in alignment with all applicable laws. We believe that embracing human differences is critical to realize our vision of a healthier world, and we recognize that a healthy and thriving community starts from within. Our values define who we are, what we stand for and how we conduct ourselves at MCW. If you believe in embracing individuality and working together according to these principles to improve health for all, then MCW is the place for you. For more information, please visit our institutional website.
MCW as an Equal Opportunity Employer and Commitment to Non-Discrimination:
The Medical College of Wisconsin (MCW) is an Equal Opportunity Employer. We are committed to fostering an inclusive community of outstanding faculty, staff, and students, as well as ensuring equal educational opportunity, employment, and access to services, programs, and activities, without regard to an individual's race, color, national origin, religion, age, disability, sex, gender identity/expression, sexual orientation, marital status, pregnancy, predisposing genetic characteristic, or military status. Employees, students, applicants or other members of the MCW community (including but not limited to vendors, visitors, and guests) may not be subjected to harassment that is prohibited by law or treated adversely or retaliated against based upon a protected characteristic.

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About Medical College of Wisconsin

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The Medical College of Wisconsin (MCW) is an industry-leading educational institution located in Milwaukee, WI, US. Being part of the medical and health services sector, MCW's primary mission is to educate and train the next generation of healthcare professionals. MCW offers a wide array of degrees and programs within medical and health sciences, covering everything from medical, graduate, pharmacy and health sciences studies, to continuing professional developments and community engagement initiatives. Founded in 1893, MCW boasts a rich, well-entrenched history in shaping the medical education landscape locally and globally. The institution's core values of knowledge-changing life underline its dedication to incorporating innovative approaches in education and research, commitment to diversity and inclusion, service to the community, integrity, stewardship, and collaboration.

Industry

Health care and social assistance

Company size

5,001 - 10,000 Employees

Headquarters location

Milwaukee, WI, US

Year founded

1893

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