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Clinical Data Associate Remote Jobs in Missouri (NOW HIRING)

Jobgether

$11.50 - $15.50/hr

Machine Learning Data Associate based in Netherlands. This is an opportunity to lead engaging, high ... This is a part-time contract position with a remote setup and scheduled sessions aligned with the ...

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Clinical Data Associate Remote information

See Missouri salary details

$11

$36

$78

How much do clinical data associate remote jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for clinical data associate remote in Missouri is $36.95, according to ZipRecruiter salary data. Most workers in this role earn between $25.87 and $46.30 per hour, depending on experience, location, and employer.

What is a clinical data associate?

A Clinical Data Associate (Remote) is a professional who manages and verifies data collected during clinical trials, working from a remote location. They ensure the accuracy, integrity, and confidentiality of clinical trial data, collaborating with clinical teams and using specialized software. Their responsibilities include data entry, cleaning, validation, and generating reports to support regulatory submissions. Remote Clinical Data Associates utilize secure systems to access and manage data, allowing them to efficiently support clinical research from anywhere.

What are the key skills and qualifications needed to thrive as a clinical data associate?

To thrive as a Clinical Data Associate (Remote), you need a strong background in life sciences, data management, and an understanding of clinical trial processes, often supported by a relevant bachelor's degree. Familiarity with electronic data capture (EDC) systems, clinical data management software, and GCP (Good Clinical Practice) certification are commonly required. Attention to detail, problem-solving abilities, and effective virtual communication are crucial soft skills for managing data integrity and collaborating with remote teams. These skills and qualifications ensure the accurate collection, validation, and reporting of clinical trial data, which is essential for regulatory compliance and successful study outcomes.

What are some common challenges faced by a clinical data associate working remotely, and how can they be managed?

Clinical Data Associates working remotely often face challenges related to communication and maintaining data quality standards across distributed teams. It can be more difficult to collaborate with clinical research coordinators, data managers, and other stakeholders without in-person interactions, making clear and timely communication essential. Utilizing secure data management platforms, participating in regular virtual meetings, and adhering strictly to data integrity protocols can help address these challenges. Proactively seeking feedback and staying updated on regulatory changes also contribute to maintaining high standards while working remotely.

What is the difference between Clinical Data Associate Remote vs Clinical Data Coordinator?

AspectClinical Data Associate RemoteClinical Data Coordinator
CredentialsBachelor's in life sciences or related field; familiarity with data management systemsBachelor's in health sciences or related field; experience with clinical data
Work EnvironmentRemote, primarily computer-basedTypically on-site or hybrid, working with clinical teams
Employer & IndustryPharmaceutical companies, CROs, biotech firmsHospitals, research institutions, clinical trial sites
Search & Comparison IntentYesYes

The Clinical Data Associate Remote and Clinical Data Coordinator roles share similarities in required education and industry usage. However, Clinical Data Associate Remote positions are primarily remote and focus on data entry and management from a distance, while Clinical Data Coordinators often work on-site, coordinating data collection and quality at clinical sites. Both roles are essential in clinical research but differ mainly in work setting and specific responsibilities.

What are popular job titles related to Clinical Data Associate Remote jobs in Missouri?

For Clinical Data Associate Remote jobs in Missouri, the most frequently searched job titles are:

What job categories do people searching Clinical Data Associate Remote jobs in Missouri look for?

The top searched job categories for Clinical Data Associate Remote jobs in Missouri are:

What cities in Missouri are hiring for Clinical Data Associate Remote jobs?

Cities in Missouri with the most Clinical Data Associate Remote job openings:

Clinical Data Associate Remote jobs near you
Infographic showing various Clinical Data Associate Remote job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $76,858 per year, or $37 per hour.

Lead Instructor: Machine Learning Data Associate

Jobgether

Remote

$11.50 - $15.50/hr

Full-time

Posted 10 days ago

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Instructor: Machine Learning Data Associate based in Netherlands.

This is an opportunity to lead engaging, high-impact virtual learning experiences for diverse audiences developing skills in machine learning and AI data workflows. You will deliver live technical instruction in German while collaborating professionally in English with program and operations teams. The role combines technical expertise, instructional leadership, and the ability to make complex AI concepts practical and accessible. You will help learners understand how data labeling influences machine learning systems, generative AI, multimodal models, and applied AI workflows. Sessions may range from smaller groups to audiences of thousands of learners in a highly interactive online environment. You will also contribute to curriculum refinement and continuous course improvement. This is a part-time contract position with a remote setup and scheduled sessions aligned with the EST/CEST time zones.

Accountabilities
  • Lead and facilitate live virtual classes for diverse learner groups, potentially ranging from 100 to more than 8,000 participants, while maintaining strong engagement and an effective learning environment.
  • Deliver technical instruction in German on machine learning data workflows, generative AI, foundation models, prompt engineering, RAG, multimodal AI, responsible AI, and related concepts.
  • Explain how data collection, annotation, labeling decisions, model training, evaluation, and deployment are connected, helping learners understand the downstream impact of their work.
  • Manage virtual classroom dynamics, including Q&A, chat activity, pacing, learner engagement, and timely delivery of planned content.
  • Adapt instructional approaches, explanations, and lesson pacing to accommodate learners with different backgrounds and levels of technical understanding.
  • Prepare thoroughly for each lecture and ensure that technical content is delivered accurately, clearly, and in an accessible manner.
  • Collaborate with program and operations teams in English to support smooth delivery, communicate updates, escalate issues, and maintain alignment on schedules and learner needs.
  • Contribute to curriculum design and continuous improvement, including suggesting edits, refining lessons, and supporting the development of hands-on learning activities.
  • Provide constructive feedback before and after sessions to strengthen course quality and learner outcomes.
  • Maintain a professional, respectful, responsive, and empathetic presence when interacting with learners, colleagues, contractors, and guest speakers.
Requirements:
  • Fluency in German sufficient to deliver all instruction and learner support professionally, combined with strong English proficiency for written communication, meetings, alignment, and issue escalation.
  • Strong practical understanding of the machine learning lifecycle, including data collection, model training, evaluation, and deployment, with the ability to explain how labeling decisions affect model behavior and downstream outputs.
  • Solid knowledge of generative AI and foundation models, including concepts such as pre-training, fine-tuning, reinforcement learning from human feedback (RLHF), and human feedback for model alignment.
  • Hands-on experience with prompt engineering, including zero-shot, one-shot, and few-shot prompting, and the ability to teach learners how to interpret requirements, identify task constraints, and evaluate output quality.
  • Working knowledge of Retrieval-Augmented Generation (RAG) and production AI workflows, including the ability to explain how to assess outputs for relevance, faithfulness, and groundedness.
  • Understanding of multimodal and cross-modal AI, including how models process and generate text, images, audio, and video, and how these capabilities influence annotation and evaluation tasks.
  • Knowledge of responsible AI, privacy, confidentiality, security, bias awareness, and transparency principles relevant to data labeling and AI workflows.
  • Demonstrated experience delivering high-quality live virtual instruction, ideally to large and diverse audiences.
  • Experience supporting technical curriculum development, lesson refinement, skills labs, or similar instructional content.
  • Strong communication, presentation, empathy, adaptability, and classroom-management skills, with the ability to make complex technical concepts easy to understand.
  • A positive and collaborative mindset, with strong attention to preparation, professionalism, responsiveness, and continuous improvement.
  • Preferred: AWS Certified AI Practitioner (AIF-C01) certification or equivalent expertise, particularly experience aligning training content with certification domains and supporting exam readiness.
Benefits:
  • Remote work: Work remotely from Romania or another location compatible with the required time zone.
  • Part-time contract: Flexible engagement structured around scheduled instructional sessions and program needs.
  • Virtual-first environment: Deliver impactful learning experiences entirely online using modern virtual classroom tools.
  • High-impact teaching: Reach diverse learner populations and contribute to workforce development in AI and data.
  • Professional collaboration: Work alongside program, operations, and instructional teams in an international environment.
  • Curriculum involvement: Contribute ideas and expertise to the development and continuous improvement of technical training content.
  • Potential schedule flexibility: Program dates and lecture times may be adjusted depending on program requirements and instructor availability.
  • Inclusive environment: Participate in a learning culture focused on respect, accessibility, diversity, and equal opportunity.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
 Why Apply Through Jobgether? 
 
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
 
 
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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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