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Remote Material Testing Laboratory Jobs in Tennessee

Koniag, Inc.

Data Scientist (Remote)

Nashville, TN · On-site +1

... briefing materials that communicate complex data science findings and model outputs clearly and ... Conduct rigorous model performance assessments, A/B testing, and experimental design analyses to ...

Conflux Systems

Packaging Engineer

Knoxville, TN · On-site +1

$34 - $50/hr

100% Remote, 2 Positions: Knoxville, TN; Seattle, CA Pay: $34 - $50/Hr, 8 AM - 5 PM, Mon to Fri, 12 ... This role focuses on designing, testing, and validating product packaging to meet regulatory ...

Varsity Tutors

NCLEX-PN Tutor

Murfreesboro, TN · Remote

$18 - $40/hr

Ability to explain computerized adaptive testing, LPN scope of practice boundaries, and Next ... Ability to identify concepts students commonly struggle with, explain material using multiple ...

Varsity Tutors

NCLEX-PN Tutor

Memphis, TN · Remote

$18 - $40/hr

Ability to explain computerized adaptive testing, LPN scope of practice boundaries, and Next ... Ability to identify concepts students commonly struggle with, explain material using multiple ...

Varsity Tutors

NCLEX-PN Tutor

Kingsport, TN · Remote

$18 - $40/hr

Ability to explain computerized adaptive testing, LPN scope of practice boundaries, and Next ... Ability to identify concepts students commonly struggle with, explain material using multiple ...

Varsity Tutors

NCLEX-PN Tutor

Knoxville, TN · Remote

$18 - $40/hr

Ability to explain computerized adaptive testing, LPN scope of practice boundaries, and Next ... Ability to identify concepts students commonly struggle with, explain material using multiple ...

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All JobsMaterial Testing Laboratory JobsRemote Material Testing Laboratory JobsRemote Material Testing Laboratory Jobs in Tennessee

Remote Material Testing Laboratory information

What is the difference between Remote Material Testing Laboratory vs Remote Materials Technician?

AspectRemote Material Testing LaboratoryRemote Materials Technician
CredentialsCertifications in materials testing, quality assuranceCertifications in materials handling, testing procedures
Work EnvironmentLaboratory settings, remote testing facilitiesField sites, remote testing locations, labs
Industry UsageManufacturing, construction, aerospaceConstruction, manufacturing, infrastructure

The Remote Material Testing Laboratory focuses on analyzing and testing materials in a lab setting, often remotely, to ensure quality and compliance. In contrast, Remote Materials Technicians perform hands-on testing and sampling at various sites, sometimes remotely, but with more fieldwork involved. Both roles require similar certifications and are vital in industries like construction and manufacturing, but their primary work environments and responsibilities differ.

What are the key skills and qualifications needed to thrive as a remote material testing laboratory technician?

To thrive as a Remote Material Testing Laboratory Technician, you need a solid background in materials science, laboratory testing procedures, and relevant academic qualifications such as a degree in engineering or materials technology. Familiarity with laboratory information management systems (LIMS), remote data acquisition tools, and various material testing instruments is typically required. Strong attention to detail, problem-solving abilities, and effective communication are crucial soft skills in this role. These competencies ensure accurate test results, reliable remote collaboration, and compliance with industry standards.

What are some common challenges faced by professionals working in a remote material testing laboratory?

Professionals working in a remote material testing laboratory often encounter challenges related to effective communication and coordination, as they collaborate with team members who may be located in different regions. Ensuring the accuracy and consistency of test results can be more complex when handling samples and data remotely. Additionally, maintaining and calibrating specialized equipment from a distance may require extra planning and support. However, with strong digital collaboration tools and well-defined protocols, these challenges can be effectively managed.

What is a remote material testing laboratory?

A Remote Material Testing Laboratory is a facility that allows for the testing and analysis of materials—such as metals, plastics, or composites—using digital tools and remote technologies. Instead of requiring physical presence, clients and engineers can access equipment, monitor tests, and analyze results online from anywhere. These labs are especially useful for organizations with distributed teams or those without access to specialized testing equipment. Remote material testing helps save time and costs while maintaining data accuracy and security. It is commonly used in industries like construction, manufacturing, and aerospace to ensure material quality and compliance with standards.
What are the most commonly searched types of Material Testing Laboratory jobs in Tennessee? The most popular types of Material Testing Laboratory jobs in Tennessee are:
What are popular job titles related to Remote Material Testing Laboratory jobs in Tennessee? For Remote Material Testing Laboratory jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Remote Material Testing Laboratory jobs in Tennessee look for? The top searched job categories for Remote Material Testing Laboratory jobs in Tennessee are:
What cities in Tennessee are hiring for Remote Material Testing Laboratory jobs? Cities in Tennessee with the most Remote Material Testing Laboratory job openings:
Remote Material Testing Laboratory jobs near you

Data Scientist (Remote)

Koniag, Inc.

Nashville, TN • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago

Job description

Koniag Services Inc., a Koniag Government Services company, is seeking a talented and innovative Data Scientist to support the development and implementation of advanced data science, machine learning, and predictive analytics solutions for our IT Call Center serving government clients. The ideal candidate is a highly analytical and technically sophisticated professional with deep expertise in data science methodologies, machine learning model development, and statistical analysis, combined with a strong understanding of IT call center operations and service delivery environments. They bring a passion for transforming complex, large-scale operational data into actionable intelligence, a collaborative and solutions-oriented work ethic, and the ability to work independently and effectively in a fully remote environment to deliver data science solutions that drive measurable improvements in IT Call Center performance, efficiency, and customer experience. Ability to obtain a government security clearance may be required to support Koniag Services Inc. and our government customers. This position is Remote.
We offer competitive compensation and an extraordinary benefits package including health, dental and vision insurance, 401K with company matching, flexible spending accounts, paid holidays, three weeks paid time off, and more.
Position Description:
The Data Scientist will be responsible for the design, development, implementation, and ongoing refinement of advanced data science and machine learning solutions that support IT Call Center operational performance, predictive intelligence, and continuous improvement objectives. This individual will work closely with program leadership, data analysts, the AWS AI Practitioner, the AWS Solutions Architect, and government stakeholders to identify high-value data science opportunities, develop and deploy analytical models, and translate complex data science outputs into clear, actionable insights that inform strategic and operational decision making. Principal responsibilities will include but are not limited to:
  • Lead the end-to-end development, implementation, and ongoing refinement of advanced data science and machine learning solutions that address high-priority IT Call Center operational challenges and performance improvement opportunities, including predictive call volume forecasting, SLA risk prediction, agent performance modeling, and customer satisfaction analytics.
  • Collaborate with program leadership, data analysts, and the AWS AI Practitioner to identify, prioritize, and scope data science use cases that deliver the highest operational value for the IT Call Center program and government customer.
  • Design and execute comprehensive data acquisition, cleaning, transformation, and feature engineering pipelines that prepare raw call center operational data from multiple sources for advanced analytical and machine learning modeling purposes.
  • Develop, train, validate, and deploy supervised, unsupervised, and reinforcement learning models using industry-leading machine learning frameworks and AWS AI and ML platform services, ensuring all models meet defined performance, accuracy, and reliability standards prior to operational deployment.
  • Design and implement natural language processing (NLP) and text analytics solutions that analyze call transcripts, ticket notes, chat logs, and customer feedback data to identify sentiment trends, topic clusters, emerging issues, and customer experience improvement opportunities.
  • Develop and maintain predictive analytics models that leverage historical and real-time call center operational data to forecast call volumes, predict staffing requirements, identify at-risk SLA performance periods, and support proactive operational decision making.
  • Partner with the AWS AI Practitioner and AWS Solutions Architect to design and implement scalable, cloud-native data science solution architectures on AWS, leveraging Amazon SageMaker, Amazon Bedrock, AWS Lambda, Amazon Kinesis, AWS Glue, and related AWS data and AI services.
  • Develop and maintain robust MLOps pipelines and practices including model versioning, automated retraining workflows, continuous integration and delivery for ML models, and comprehensive model performance monitoring and drift detection frameworks.
  • Design and develop advanced data visualizations, analytical reports, and executive-level briefing materials that communicate complex data science findings and model outputs clearly and compellingly to non-technical program leadership and government stakeholders.
  • Collaborate with data analysts to ensure data science outputs are integrated effectively into operational reporting frameworks, performance dashboards, and decision support tools used by program leadership and call center operations staff.
  • Conduct rigorous model performance assessments, A/B testing, and experimental design analyses to evaluate the operational impact of deployed data science solutions and inform continuous model improvement activities.
  • Ensure all data science solution development and deployment activities comply with applicable federal security requirements, data privacy regulations, responsible AI governance standards, AWS GovCloud policies, and FedRAMP authorization requirements.
  • Provide technical guidance, mentorship, and subject matter expertise to data analysts and junior technical team members on data science methodologies, machine learning concepts, statistical analysis techniques, and AWS AI and ML service capabilities.
  • Develop and maintain comprehensive technical documentation for all data science solutions including model design documents, feature engineering specifications, training and validation results, deployment procedures, and operational monitoring runbooks.
  • Stay current on emerging data science methodologies, machine learning research, AWS AI and ML platform updates, and industry best practices, proactively identifying opportunities to leverage new techniques and technologies to enhance IT Call Center operational intelligence and performance.
  • Support business development activities as needed, including contributing to proposal efforts with data science capability narratives, technical solution concepts, analytical methodology descriptions, and relevant past performance documentation.

Education and Experience:
Required:
  • Master's degree in Data Science, Statistics, Mathematics, Computer Science, Machine Learning, or a related quantitative field from an accredited college or university. Relevant experience may be considered in lieu of an advanced degree.
  • 4+ years of hands-on experience in a data science role, with demonstrated experience designing, developing, and deploying machine learning models and advanced analytical solutions in a structured operational environment.
  • Demonstrated experience developing and deploying NLP, predictive analytics, and machine learning solutions using Python and industry-leading ML frameworks.
  • Experience leveraging AWS AI and ML services including Amazon SageMaker, Amazon Comprehend, Amazon Transcribe, or equivalent cloud-based ML platform services.
  • Experience working with large, complex, multi-source datasets in a structured analytical environment.

Preferred:
  • Doctoral degree (Ph.D.) in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.
  • Prior experience applying data science methodologies within a federal government contracting or AWS GovCloud environment.
  • Experience supporting data science solution development for an IT call center, service desk, or IT managed services program.
  • AWS Certified Machine Learning - Specialty certification or AWS Certified AI Practitioner certification.
  • Experience working in a fully remote data science role within a government contracting environment.

Required Skills and Competencies:
  • Exceptional communication skills in English - both written and oral - with the ability to explain complex data science concepts, model outputs, and analytical findings clearly and compellingly to non-technical program leadership, government stakeholders, and cross-functional team members in a remote work environment.
  • Expert-level proficiency in Python for data science and machine learning development, including extensive experience with core data science libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, SpaCy, and Matplotlib.
  • Deep expertise in machine learning theory and practice, including supervised learning, unsupervised learning, reinforcement learning, ensemble methods, neural networks, deep learning architectures, and model evaluation and validation methodologies.
  • Advanced proficiency in natural language processing (NLP) and text analytics techniques, including tokenization, named entity recognition, sentiment analysis, topic modeling, text classification, and transformer-based language model fine-tuning and deployment.
  • Demonstrated proficiency in Amazon SageMaker for end-to-end ML pipeline development, including data preparation, model training, hyperparameter tuning, model deployment, and automated model monitoring and retraining.
  • Strong proficiency in SQL and NoSQL data querying languages for extracting, transforming, and analyzing large-scale datasets from relational databases, data warehouses, and ITSM platforms.
  • Demonstrated experience designing and implementing MLOps practices and pipelines, including model versioning, CI/CD for ML, automated retraining workflows, and model performance drift detection and alerting.
  • Advanced proficiency in data visualization tools and libraries including Microsoft Power BI, Tableau, Matplotlib, Seaborn, or Plotly for communicating complex data science findings and model outputs to technical and non-technical audiences.
  • Strong understanding of statistical analysis concepts and methods including hypothesis testing, regression analysis, time series analysis, Bayesian inference, and experimental design as applied to operational performance data.
  • Demonstrated ability to manage multiple complex data science initiatives simultaneously, work independently with minimal supervision, and deliver high-quality analytical outputs within established timelines in a remote work environment.
  • Ability to obtain and maintain a government security clearance as required.

Desired Skills and Competencies:
  • Active government security clearance (Secret or higher).
  • AWS Certified Machine Learning - Specialty certification.
  • AWS Certified AI Practitioner certification.
  • AWS Certified Solutions Architect - Associate certification demonstrating cloud architecture knowledge relevant to data science solution deployment.
  • Experience designing and implementing data science solutions within an AWS GovCloud environment in support of federal government FedRAMP authorization and data privacy requirements.
  • Familiarity with federal IT security frameworks and compliance requirements such as NIST SP 800-53, FedRAMP, FISMA, and emerging federal AI governance frameworks as they relate to data science solution design and deployment.
  • Experience with Amazon Bedrock, large language models (LLMs), and generative AI application development for intelligent automation and conversational AI use cases within a government IT service delivery context.
  • Familiarity with responsible AI principles, AI ethics frameworks, explainable AI (XAI) methodologies, and algorithmic bias detection and mitigation strategies as they apply to data science solution development in a federal government environment.
  • Experience with data engineering tools and platforms including AWS Glue, Amazon Kinesis, Amazon Redshift, Apache Spark, or equivalent big data processing and pipeline management technologies.
  • Experience with graph analytics, anomaly detection, or forecasting methodologies as applied to IT service delivery operational data.
  • Familiarity with reinforcement learning from human feedback (RLHF) and fine-tuning techniques for large language model customization in a government IT context.
  • Experience with A/B testing frameworks, causal inference methodologies, and experimental design for evaluating the operational impact of deployed data science solutions.
  • Knowledge of containerization and orchestration technologies such as Docker and Kubernetes as they relate to scalable ML model deployment and management in a cloud-native environment.
  • Experience contributing to business development efforts including proposal writing, data science capability development, analytical methodology narratives, and past performance documentation.

Our Equal Employment Opportunity Policy:
The company is an equal opportunity employer. The company shall not discriminate against any employee or applicant because of race, color, religion, creed, ethnicity, sex, sexual orientation, gender or gender identity (except where gender is a bona fide occupational qualification), national origin or ancestry, age, disability, citizenship, military/veteran status, marital status, genetic information or any other characteristic protected by applicable federal, state, or local law. We are committed to equal employment opportunity in all decisions related to employment, promotion, wages, benefits, and all other privileges, terms, and conditions of employment.
The company is dedicated to seeking all qualified applicants. If you require an accommodation to navigate or to apply to a position on our website, please contact Heaven Wood via e-mail at accommodations@koniag-gs.com or by calling 703-488-9377 to request accommodations.
Koniag Government Services (KGS) is an Alaska Native Owned corporation supporting the values and traditions of our native communities through an agile employee and corporate culture that delivers Enterprise Solutions, Professional Services and Operational Management to Federal Government Agencies. As a wholly owned subsidiary of Koniag, we apply our proven commercial solutions to a deep knowledge of Defense and Civilian missions to provide forward leaning technical, professional, and operational solutions. KGS enables successful mission outcomes for our customers through solution-oriented business partnerships and a commitment to exceptional service delivery. We ensure long-term su
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About Koniag

Sourced by ZipRecruiter

Industry

Investment management and consulting services

Company size

501 - 1,000 Employees

Headquarters location

Kodiak, AK, US

Year founded

1972

Social media

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