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Sample Management Scientist Jobs in Texas (NOW HIRING)

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

TX · On-site

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... sampling/resampling techniques. * Strong expertise in geospatial analytics and LiDAR data ... Excellent analytical, communication, and stakeholder management skills. Roles & Responsibilities

... Laboratory Information Management Software (LIMS). Scan and attach associated documents ... science and or math courses preferred EXPERIENCE One year of laboratory or chemical material ...

Showing results 21-40

Sample Management Scientist information

What are some common challenges faced by sample management scientists in maintaining sample integrity throughout the research process?

Sample Management Scientists often encounter challenges such as preventing sample contamination, ensuring proper labeling and documentation, and maintaining optimal storage conditions. These responsibilities require meticulous attention to detail and strict adherence to protocols in order to guarantee the reliability of research results. Additionally, coordinating with research teams and adapting to evolving project requirements can be demanding, but these challenges also offer opportunities for developing problem-solving skills and process improvements.

What is a sample management scientist?

Sample Management Scientists are professionals responsible for overseeing the collection, storage, tracking, and distribution of biological or chemical samples in laboratories or research facilities. They ensure that samples are handled according to strict protocols to maintain their integrity and traceability. Their work supports research, drug discovery, clinical trials, and other scientific processes by maintaining high standards for sample quality and data accuracy. Sample Management Scientists often use specialized software and follow rigorous documentation procedures to comply with regulatory requirements.

What is the difference between Sample Management Scientist vs Laboratory Technician?

AspectSample Management ScientistLaboratory Technician
Required CredentialsBachelor's degree in life sciences or related field; experience in sample handlingAssociate's degree or certification; basic laboratory training
Work EnvironmentResearch labs, pharmaceutical companies, biotech firmsClinical labs, research facilities, manufacturing plants
Employer & Industry UsageUsed in research, development, and quality control sectorsCommon in clinical testing, sample processing, and routine lab tasks

The Sample Management Scientist focuses on overseeing the proper handling, storage, and documentation of samples in research and development settings. In contrast, the Laboratory Technician performs routine testing and sample preparation tasks. While both roles require laboratory experience, the Scientist typically has more specialized knowledge in sample lifecycle management, making them more involved in data integrity and sample tracking systems.

What are the key skills and qualifications needed to thrive as a sample management scientist, and why are they important?

To thrive as a Sample Management Scientist, you need a background in laboratory science, strong organizational abilities, and often a degree in chemistry, biology, or a related field. Familiarity with Laboratory Information Management Systems (LIMS), sample tracking software, and regulatory compliance standards is typical. Attention to detail, problem-solving skills, and effective communication help ensure accurate sample handling and collaboration with research teams. These competencies are crucial for maintaining data integrity, meeting project timelines, and supporting reliable scientific results.

What job categories do people searching Sample Management Scientist jobs in Texas look for?

The top searched job categories for Sample Management Scientist jobs in Texas are:

What cities in Texas are hiring for Sample Management Scientist jobs?

Cities in Texas with the most Sample Management Scientist job openings:

Infographic showing various Sample Management Scientist job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Full-time

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Job description

Required Skills
  • 10+ years of hands-on experience in Applied Data Science, Analytics Engineering, and Systems Modeling.
  • 5+ years of client-facing, consulting, or business development experience delivering analytics solutions.
  • Expertise in statistical modeling, machine learning, and predictive analytics.
  • Strong proficiency with Python, scikit-learn, statsmodels, PyTorch, and TensorFlow.
  • Experience in time-series forecasting, causal inference, feature engineering, and advanced data sampling/resampling techniques.
  • Strong expertise in geospatial analytics and LiDAR data processing.
  • Hands-on experience with ArcGIS, PostGIS, GeoPandas, GDAL/OGR, PDAL, and related geospatial libraries.
  • Experience working with vector, raster, point-cloud, and sensor datasets.
  • Excellent analytical, communication, and stakeholder management skills.
Roles & Responsibilities
  • Design and develop advanced machine learning and statistical models to solve complex business problems.
  • Build predictive models, time-series forecasting solutions, and causal inference frameworks.
  • Perform feature engineering, data preparation, and advanced sampling techniques for large-scale datasets.
  • Develop geospatial analytics and LiDAR processing solutions using industry-standard tools and libraries.
  • Analyze vector, raster, point-cloud, and sensor data to generate actionable insights.
  • Partner with business stakeholders to scope, design, and deliver data science solutions.
  • Present analytical findings and recommendations to technical and business audiences.
  • Optimize model performance, scalability, and deployment in production environments.
  • Mentor data scientists and promote best practices in analytics and machine learning.
  • Support innovation initiatives through advanced analytics and AI-driven solutions.