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Contract Data Annotation Jobs in Ohio (NOW HIRING)

Philips Iberica SAU

$90 - $120/hr

Leads site/KOL engagement and all site‑facing activities (protocol communication, contracts ... data quality, completeness, annotation integrity, adherence to protocol and traceability, while ...

Philips International

$90 - $130/hr

Leads site/KOL engagement and all site‐facing activities (protocol communication, contracts ... data quality, completeness, annotation integrity, adherence to protocol and traceability, while ...

All JobsContract Data Annotation JobsContract Data Annotation Jobs in Ohio

Contract Data Annotation information

What is a contract data annotation?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

What are the key skills and qualifications needed to thrive as a contract data annotation specialist?

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

Is data annotation still hiring?

Data annotation roles are currently in demand as companies continue to develop AI and machine learning models. Many positions are available for remote work, often requiring basic computer skills and attention to detail, with some roles offering flexible schedules. Job availability can vary by industry and region, so checking specific job boards is recommended.

Is it hard to get hired for contract data annotation?

Contract data annotation jobs are generally accessible to individuals with basic computer skills and attention to detail. The hiring process often involves completing a skills test or sample annotation task, and some roles may require familiarity with specific tools or platforms. Competition can vary depending on the demand and the company's requirements, but many positions are available for entry-level candidates.

What are the most commonly searched types of Data Annotation jobs in Ohio?

The most popular types of Data Annotation jobs in Ohio are:

What are popular job titles related to Contract Data Annotation jobs in Ohio?

For Contract Data Annotation jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Contract Data Annotation jobs in Ohio look for?

The top searched job categories for Contract Data Annotation jobs in Ohio are:

What cities in Ohio are hiring for Contract Data Annotation jobs?

Cities in Ohio with the most Contract Data Annotation job openings:

Contract Data Annotation jobs near you

Clinical Development Scientist

Philips Iberica SAU

On-site

$90 - $120/hr

Other

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

Job description

Job Title

Clinical Development Scientist

Job DescriptionJob Responsibilities
  • Owns and drives end‑to‑end clinical evidence strategy, defining and linking clinical need, value, TPP, claims, endpoints, and evidence to regulatory acceptance and post‑market requirements with full lifecycle traceability (AD -> PDLM -> PMS).
  • Leads clinical development in cross‑functional AD and PDLM core teams and drives program governance and cross‑project integration enabling global alignment.
  • Owns clinical study design, protocol development, and execution—driving end‑to‑end delivery (kick‑off to results) with optimal data strategy, data integrity, audit readiness, and proactive risk and timeline management.
  • Leads site/KOL engagement and all site‑facing activities (protocol communication, contracts, training) in collaboration with Clinical Science/CPM to ensure compliant execution, protocol adherence, and consistent understanding of product and data requirements.
  • Owns end‑to‑end data strategy and oversees data management in collaboration with data/engineering teams, ensuring data quality, completeness, annotation integrity, adherence to protocol and traceability, while resolving complex data challenges.
  • Collaborates with data/engineering teams on data infrastructure (catalogues, systems) for structured access, traceability.
  • Operationalizes real‑world data by identifying, integrating, and governing data relevance, reliability and scientific validity of diverse data sources, and leads CER and PMCF analytics to generate and continuously assess clinical evidence on safety, performance, and benefit–risk for patient safety and in accordance with regulations and guidance documents.
  • Defines claims validation strategies and leads continuous post‑market evidence surveillance (PMCF/PMS), translating insights into updated claims, regulatory submissions, and expansion of clinical value, indications, and market positioning.
  • Authors and oversees core clinical and regulatory documents (study protocols, CDMA, data strategies, CSRs, CERs, PMCF), ensuring compliant, evidence‑based, and traceable outputs, including integration into IFU and regulatory submissions (e.g., 510k, Technical Documentation, NMPA etc).
  • Drives program risk management and knowledge sharing to optimize execution and evidence generation, and bridges regional and global teams.
  • Communicates insights and aligns stakeholders, builds KOL partnerships, and supports informed decision‑making.
  • Drives scientific dissemination by translating clinical and real‑world evidence into publications, presentations, and competitive insights.
  • Drives structured project management via ADO/Azure, aligning cross‑functional tasks, tracking dependencies, and ensuring clear ownership, prioritization, and timely execution.
Qualifications
  • Medical degree (physician) / Doctor of Medicine, or Medical Technical degree, or a Life Science degree, or a Quantitative Science degree (e.g., Medicine, Technical Medicine, Biomedical Engineering, Biotechnology, Epidemiology, Health Informatics, Data Science).
  • Residency & Advanced Training in Diagnostic Radiology/Ultrasound domain
  • Experience with ultrasound imaging.
  • Experience with developing AI-features in Radiology/Ultrasound.
  • Experience with developing AI‑based medical devices.
  • Experience in Clinical Development / Clinical Research.
  • Experience in clinical evidence communication, research and analysis.
  • Experience in Medical Writing (CER, CSR, PMCF) and/or Scientific Publications is nice to have
  • Experience in MedTech, Healthcare Research, Real-World data analytics, Epidemiology, or related fields.
  • Experienced in regulatory compliance, process improvement and project management
  • Experience with data tools (R, Python, Power BI, Tableau, Git) is nice to have
Preferred Skills
  • Regulatory Compliance
  • Clinical Evaluation and PMCF methodologies
  • Clinical Evidence Generation Strategy
  • Medical and Regulatory Writing (CER, CSR, reports)
  • Data Analysis and Interpretation
  • Quantitative and Real‑World Evidence Methods
  • Project and Program Management
  • Strategic Planning and Business Acumen
  • KPI and Performance Management
  • Document Review and Audit Readiness
  • Continuous Improvement
  • Medical Terminology
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