ZipRecruiter

Log In

2

Remote Clinical Data Manager Jobs in Nevada (NOW HIRING)

previous page

Showing results 41-60

All JobsClinical Data JobsRemote Clinical Data Manager JobsRemote Clinical Data Manager Jobs in Nevada

Remote Clinical Data Manager information

See Nevada salary details

$20

$58

$83

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

As of Aug 18, 2026, the average hourly pay for remote clinical data manager in Nevada is $58.21, according to ZipRecruiter salary data. Most workers in this role earn between $46.01 and $69.28 per hour, depending on experience, location, and employer.

What is a remote clinical data manager?

A Remote Clinical Data Manager is a professional responsible for overseeing the collection, processing, and management of clinical trial data while working from a remote location. They ensure that the data collected during clinical studies is accurate, complete, and compliant with regulatory standards. Their key tasks include database design, data cleaning, and collaborating with clinical teams to resolve data discrepancies. Remote Clinical Data Managers often use specialized software and work closely with other research professionals to maintain data integrity and support successful clinical trial outcomes.

What does a remote clinical data manager do?

Remote clinical data managers collect, compile, and organize data from research projects and clinical trials. They perform their job duties from home or another location outside of the office with internet capability. In this career, you are responsible for recording relevant information and results from clinical trials and making sure they are logged accurately and secured correctly. You examine the research process, checking that the data meets industry regulations and requirements for clinical testing. Once the trial begins, you evaluate the data to ensure researchers collect the right information as they conduct their tests, experiments, or research. You collaborate remotely with researchers to produce reports, statistics, and charts. Remote clinical data managers work with pharmaceutical companies, healthcare providers, government agencies, and research institutions.

How does a remote clinical data manager typically collaborate with clinical research teams and ensure data integrity across different locations?

As a Remote Clinical Data Manager, you'll frequently coordinate with cross-functional teams, including clinical research associates, biostatisticians, and project managers, using digital communication tools and project management platforms. Ensuring data integrity involves setting up secure data management systems, implementing data validation checks, and conducting regular data reviews. You'll participate in virtual meetings to discuss data queries, timelines, and protocol updates, and often provide training or support to site staff on electronic data capture (EDC) systems. Maintaining clear communication and thorough documentation is essential for successful remote collaboration and high-quality data management.

What are the key skills and qualifications needed to thrive as a remote clinical data manager, and why are they important?

To thrive as a Remote Clinical Data Manager, you need expertise in clinical data management, knowledge of regulatory guidelines (such as GCP), and a degree in life sciences or a related field. Familiarity with electronic data capture (EDC) systems, clinical trial management software, and certifications like CCDM are typically required. Strong attention to detail, problem-solving abilities, and effective remote communication skills help you excel in this position. These competencies ensure accurate data collection, regulatory compliance, and efficient collaboration within dispersed clinical research teams.

What is the difference between Remote Clinical Data Manager vs Remote Clinical Research Associate?

AspectRemote Clinical Data ManagerRemote Clinical Research Associate
CredentialsBachelor's in Life Sciences, Biostatistics, or related field; experience with data management systemsBachelor's in Life Sciences, Nursing, or related field; experience in monitoring and site management
Work EnvironmentData analysis, database management, and quality controlMonitoring clinical sites, ensuring protocol adherence, and site communication
Industry UsagePharmaceutical, biotech, and clinical research organizationsPharmaceutical, biotech, and contract research organizations
Search & Comparison IntentFocuses on data management roles in clinical trialsFocuses on site monitoring and trial oversight roles

The main difference is that Remote Clinical Data Managers handle data collection, validation, and database management, while Remote Clinical Research Associates focus on site monitoring and ensuring trial compliance. Both roles are essential in clinical research but serve different functions within the trial process.

More about Remote Clinical Data Manager jobs

What are the most commonly searched types of Remote Clinical Data jobs in Nevada?

The most popular types of Remote Clinical Data jobs in Nevada are:

What are popular job titles related to Remote Clinical Data Manager jobs in Nevada?

For Remote Clinical Data Manager jobs in Nevada, the most frequently searched job titles are:

What job categories do people searching Remote Clinical Data Manager jobs in Nevada look for?

The top searched job categories for Remote Clinical Data Manager jobs in Nevada are:

Remote Clinical Data Manager jobs near you
Infographic showing various Remote Clinical Data Manager job openings in Nevada as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $121,085 per year, or $58.2 per hour.

AI Training Specialist - Cheminformatics

micro1 AI

Sparks, NV • Remote

$80 - $110/hr

Part-time

Posted 15 days ago

Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customer’s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrödinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.

Apply