Research Data Coordinator Jobs
Research Data Coordinator jobs are open across academic medical centers, pharmaceutical companies, clinical research organizations, and government agencies, from entry-level coordinator to senior and lead roles, with specializations in clinical trial data management, epidemiological research, and biostatistics support. See the openings below and apply to the ones that match your experience.
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Showing 5 of 38+ Research Data Coordinator jobs
General Information
- United States of America - North Carolina - Morrisville
Why Work at Lenovo
Description and Requirements
AI Data Intelligence Staff Researcher
Role Overview
Lenovo is seeking an AI Data Intelligence Staff Researcher to develop intelligent, efficient, and reliable AI solutions for Hybrid AI computing and data infrastructure.
In this role, you will use machine learning, deep learning, data science, and software engineering to improve system performance, reliability, scalability, and resource efficiency.
You will collaborate with research, engineering, and product teams to turn innovative AI research into practical solutions for Lenovo's Enterprise AI and Personal AI products.
What You'll Do
AI/ML Research: Research and develop machine learning, deep learning, and AI solutions for computing and data infrastructure.
Data Analysis: Analyze large datasets using statistical methods, predictive modeling, and data science techniques.
System Optimization: Develop AI solutions to improve system performance, resource allocation, workload management, and reliability.
Predictive Analytics: Use time-series analysis, anomaly detection, and forecasting to identify system issues and predict failures.
Advanced AI Research: Explore reinforcement learning, causal inference, knowledge graphs, and graph neural networks.
Software Development: Build scalable data pipelines, AI applications, APIs, and production-quality software.
Research & Testing: Conduct experiments, evaluate model performance, and validate AI solutions.
Collaboration: Work with research, engineering, and product teams to implement AI solutions.
Innovation: Contribute to research publications, patents, technical reports, and reusable software.
Minimum Qualifications
Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.
Strong understanding of machine learning, deep learning, statistical modeling, or data science.
Programming experience with Python, C++, or a similar language.
Experience with AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, NumPy, or pandas.
Knowledge of probability, statistics, linear algebra, and optimization.
Relevant AI/ML experience through academic projects, internships, or research.
Strong analytical, problem-solving, programming, and communication skills.
Candidates should also have knowledge or experience in at least two of the following areas:
Machine learning or deep learning
Statistical modeling or predictive analytics
Time-series analysis or signal processing
Anomaly detection or fault diagnosis
Causal inference or optimization
Knowledge graphs or graph machine learning
Reinforcement learning
Large-scale data analytics or AI systems
Preferred Qualifications
Research or project experience in advanced machine learning, deep learning, generative AI, or reinforcement learning.
Experience with forecasting, anomaly detection, causal inference, graph neural networks, or predictive analytics.
Experience building scalable AI applications or production-quality software.
Familiarity with cloud platforms, distributed computing, GPU computing, or AI infrastructure.
Research publications, patents, open-source contributions, internships, or significant academic projects.
- United States of America - North Carolina - Morrisville
- United States of America
- United States of America - North Carolina
- United States of America - North Carolina - Morrisville
General Information
- United States of America - North Carolina - Morrisville
Why Work at Lenovo
Description and Requirements
AI Data Intelligence Staff Researcher
Role Overview
Lenovo is seeking an AI Data Intelligence Staff Researcher to develop intelligent, efficient, and reliable AI solutions for Hybrid AI computing and data infrastructure.
In this role, you will use machine learning, deep learning, data science, and software engineering to improve system performance, reliability, scalability, and resource efficiency.
You will collaborate with research, engineering, and product teams to turn innovative AI research into practical solutions for Lenovo's Enterprise AI and Personal AI products.
What You'll Do
AI/ML Research: Research and develop machine learning, deep learning, and AI solutions for computing and data infrastructure.
Data Analysis: Analyze large datasets using statistical methods, predictive modeling, and data science techniques.
System Optimization: Develop AI solutions to improve system performance, resource allocation, workload management, and reliability.
Predictive Analytics: Use time-series analysis, anomaly detection, and forecasting to identify system issues and predict failures.
Advanced AI Research: Explore reinforcement learning, causal inference, knowledge graphs, and graph neural networks.
Software Development: Build scalable data pipelines, AI applications, APIs, and production-quality software.
Research & Testing: Conduct experiments, evaluate model performance, and validate AI solutions.
Collaboration: Work with research, engineering, and product teams to implement AI solutions.
Innovation: Contribute to research publications, patents, technical reports, and reusable software.
Minimum Qualifications
Master's or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Electrical Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.
Strong understanding of machine learning, deep learning, statistical modeling, or data science.
Programming experience with Python, C++, or a similar language.
Experience with AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn, NumPy, or pandas.
Knowledge of probability, statistics, linear algebra, and optimization.
Relevant AI/ML experience through academic projects, internships, or research.
Strong analytical, problem-solving, programming, and communication skills.
Candidates should also have knowledge or experience in at least two of the following areas:
Machine learning or deep learning
Statistical modeling or predictive analytics
Time-series analysis or signal processing
Anomaly detection or fault diagnosis
Causal inference or optimization
Knowledge graphs or graph machine learning
Reinforcement learning
Large-scale data analytics or AI systems
Preferred Qualifications
Research or project experience in advanced machine learning, deep learning, generative AI, or reinforcement learning.
Experience with forecasting, anomaly detection, causal inference, graph neural networks, or predictive analytics.
Experience building scalable AI applications or production-quality software.
Familiarity with cloud platforms, distributed computing, GPU computing, or AI infrastructure.
Research publications, patents, open-source contributions, internships, or significant academic projects.
- United States of America - North Carolina - Morrisville
- United States of America
- United States of America - North Carolina
- United States of America - North Carolina - Morrisville
Research Data Coordinator Jobs by Experience Level
See All 38 Research Data Coordinator Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsResearch Data Coordinator Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Education
What Employers Look For
The qualifications that appear most often in research data coordinator jobs.
- Bachelor's degree in a life science, public health, or related field required
- Experience with clinical data management systems such as REDCap, Medidata Rave, or Oracle Clinical
- Familiarity with Good Clinical Practice guidelines and IRB submission processes
- Proficiency in data cleaning and quality control using SAS, R, or SPSS
- Knowledge of FDA regulations and HIPAA data privacy requirements
- Experience supporting regulatory submissions, case report form design, or study documentation
Tips for Your Research Data Coordinator Job Search
Tailor your resume to the protocol
Highlight the specific database systems you've used, such as REDCap, SAS, or SPSS, and name the study types you've supported. Hiring managers scan for protocol compliance experience and IRB familiarity, so make those visible in your first few bullet points.
Apply early to roles that fit
Migrate Mate lists research data coordinator openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings by study phase
Filter for roles that name the clinical trial phase or research stage you know best. A coordinator with Phase II oncology experience is a stronger match for a Phase II cardiology role than a generalist, so targeting by phase makes your application more competitive.
Get your CCRP or CCDM certification first
Many academic medical centers and CROs list the Certified Clinical Research Professional or Certified Clinical Data Manager credential as preferred. Earning one before you apply moves you past the initial screen and signals you understand GCP and regulatory requirements.
Prepare for a data audit exercise
Many interview processes for this role include a live or take-home exercise where you clean a messy dataset or identify protocol deviations. Practice flagging missing values, inconsistent date formats, and out-of-range entries in a sample spreadsheet before your interview.
Negotiate start date around your certifications
If you're mid-way through a SOCRA or ACRP certification exam cycle when you receive an offer, ask for a start date that lets you complete it. Most research institutions prefer you start credentialed and will accommodate a two-to-four-week adjustment.
Research Data Coordinator Jobs: Frequently Asked Questions
Which companies are hiring the most research data coordinators?
The most active employers for research data coordinators right now are Moffitt Cancer Center, Apple, and Virginia Tech, and the most openings are in Florida, California, and Texas, based on current listings on Migrate Mate as of November 2026. Academic medical centers and contract research organizations consistently account for the largest share of open roles.
How many research data coordinator jobs are remote?
About 73% of research data coordinator openings are fully remote or hybrid as of November 2026, with availability varying by institution type. Data entry, quality control, and database management tasks are most commonly approved for remote work, while roles that require on-site participant contact or biospecimen handling are almost always in-person.
How do you become a research data coordinator?
Start with a bachelor's degree in a life science, public health, statistics, or a related field. Gain hands-on experience through a research assistant role, internship, or clinical trial support position where you work directly with data collection tools and study protocols. Learn a clinical data management system such as REDCap, then pursue a CCRP or CCDM certification to strengthen your application for coordinator-level roles.
Can you get hired as a research data coordinator with little experience?
Yes, entry-level research data coordinator roles exist, particularly at universities and academic hospitals that run ongoing longitudinal studies and need coordinators for data entry and quality checks. Demonstrating familiarity with any clinical or scientific database, even from a class project or volunteer research position, and showing you understand IRB consent processes will set you apart from candidates with no research exposure at all.
What does the research data coordinator interview process look like?
Most hiring processes include an initial phone screen with HR, followed by a technical interview with the principal investigator or data management lead who will ask about your experience with specific databases, regulatory requirements, and data cleaning methods. Some institutions add a practical exercise where you review a sample dataset or case report form for errors. A final round with the broader research team is common before an offer is extended.
Where can I find and apply to research data coordinator jobs?
You can find and apply to research data coordinator jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your study area, database experience, and preferred setting, then apply directly to each listing that fits.
See All 38 Research Data Coordinator Jobs
Find roles that match your experience and apply in just a few clicks.
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