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Senior Data Annotation Analyst Jobs in West Virginia

WV

$77K - $97K/yr

The Senior Data Analyst will provide support to key projects through data collection, computational support, and data interpretation and reporting, and will ensure data accuracy and consistent ...

New

Senior Data Analyst

Charleston, WV · On-site

$100K - $120K/yr

The Senior Data Analyst will mentor junior analysts, collaborate with cross-functional teams, and serve as a key contributor in advancing our data-driven culture. What You'll Do * Lead advanced data ...

Senior Data Architect

Clarksburg, WV · Remote

$66 - $88.25/hr

Senior Data Architect ID: 1613 Location: Clarksburg, WV More about this job > Description Data ... Develop analytical tools and reporting solutions that support data ingest analysis, data management ...

Senior Data Architect

Clarksburg, WV · On-site

$66 - $88.25/hr

The Senior Data Architect will provide technical leadership in database architecture, data ... Develop analytical tools and reporting solutions that support data ingest analysis, data management ...

Senior Data Scientist

Kearneysville, WV · On-site

$133K - $169K/yr

GovCIO is seeking a Senior Data Scientist to support a critical government computer system for the ... Develop and optimize robust data pipelines, automated ETL/ELT workflows, and analytical services to ...

Senior Data Engineer

WV · On-site +1

$95K - $129K/yr

Data Analysis, Data Analytics, Data Lake, Data Warehousing (DW), ETL Design Certifications: None Experience: 7 + years of related experience US Citizenship Required: No Senior Data Engineer Seize ...

Senior Data Architect

WV · On-site +1

$195K - $264K/yr

... analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support ... The Sr. Data Architect will execute the following responsibilities: Data Platform & Architecture

Data Analyst Senior

WV · On-site +1

$93K - $115K/yr

No The Data Analyst Senior supports the data collection and analysis efforts for monitoring the implementation of a government program with respect to the care and placement of participants in a ...

Posted today

WV

$200K/yr

Define annotation guidelines, taxonomies, and edge-case protocols for each labeling program ... Identify and remediate mislabeled data in existing datasets. * Platform & tooling : Serve as the ...

$98K - $133K/yr

The Senior Data Engineer will report directly to the Senior Vice President of Enterprise ... Architect scalable ETL/ELT pipelines to efficiently transform raw data into structured, analytics ...

Job Title Senior Data Science Consultant, Insurance - Remote Requisition Number R7828 Senior Data ... Beyond delivering high-impact analytics, this person will help strengthen CSAA's internal ...

Sr. Healthcare Data Analyst (Medicaid)

WV · On-site +1

$106K - $143K/yr

As a Sr. Healthcare Data Analyst you will help ensure today is safe and tomorrow is smarter. The Sr. Healthcare Data Analyst will be a collaborative part of our team to support the Centers for ...

No As the Senior Data Scientist for Machine Learning supporting the Healthcare Fraud Prevention ... Graph or network analytics, entity resolution and record linkage for identifying collusive ...

Join us! As a Senior Data Scientist at Hagerty, you'll build the customer identity and ... Source and analyze features from Snowflake, SQL Server, and AWS RDS Postgres, and work with Data ...

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Showing results 1-20

Senior Data Annotation Analyst information

What is a senior data annotation analyst?

Senior Data Annotation Analysts are experienced professionals who oversee the process of labeling and tagging data, such as text, images, or audio, to train machine learning models. They are responsible for ensuring high-quality annotations, developing guidelines, and often mentoring junior annotators. Their work is crucial for the success of AI and machine learning projects, as accurate data annotation directly impacts model performance. Senior analysts also collaborate with data scientists and engineers to refine annotation processes and improve data quality.

What are the key skills and qualifications needed to thrive as a senior data annotation analyst?

To thrive as a Senior Data Annotation Analyst, you need expertise in data labeling, analytical thinking, and a strong understanding of machine learning concepts, often supported by a relevant degree or significant experience in data operations. Familiarity with annotation platforms (like Labelbox or Supervisely), data management tools, and quality assurance processes is typically required. Attention to detail, problem-solving, and the ability to communicate feedback effectively are crucial soft skills for this role. These competencies ensure high-quality data sets that drive accurate machine learning models and improve project outcomes.

How does a senior data annotation analyst typically collaborate with machine learning engineers and data scientists?

As a Senior Data Annotation Analyst, you will often work closely with machine learning engineers and data scientists to ensure that labeled data meets project requirements and quality standards. You may participate in meetings to discuss annotation guidelines, clarify ambiguous cases, and provide feedback on data challenges that arise. Your expertise in annotation tools and processes helps streamline workflows and ensures that the annotated datasets are reliable, which is critical for model training and evaluation. Collaboration is key, and you'll be expected to communicate effectively across teams to address issues and continuously improve the data pipeline.

What is the difference between Senior Data Annotation Analyst vs Data Annotation Specialist?

AspectSenior Data Annotation AnalystData Annotation Specialist
CredentialsBachelor's degree in related field, experience in data annotationHigh school diploma or equivalent, entry-level experience
Work EnvironmentCollaborative teams, project management, quality assuranceIndividual tasks, data labeling, basic quality checks
Industry UsageTech, AI, machine learning companiesAI startups, data labeling firms, research projects

The Senior Data Annotation Analyst typically has more experience, handles complex annotation projects, and oversees quality control, whereas the Data Annotation Specialist focuses on basic labeling tasks. Both roles are essential in AI data preparation, but the senior analyst often leads projects and ensures standards are met.

Does data annotation actually pay well?

Data annotation analysts typically earn hourly wages that are close to minimum wage or slightly above, with pay varying based on experience, location, and the complexity of tasks. While some roles offer higher pay for specialized skills or certifications, overall compensation is generally modest compared to other tech roles.

Is data annotation still hiring?

Data annotation roles, including senior positions, are actively hiring as companies expand their AI and machine learning projects. These jobs often require attention to detail and familiarity with annotation tools, and they are available in both remote and on-site formats. Demand remains steady due to ongoing growth in AI data needs.

What does a senior data annotation analyst do?

A senior data annotation analyst is responsible for reviewing, labeling, and validating data to ensure accuracy for machine learning models. They often use annotation tools and may oversee junior team members, ensuring data quality and consistency in projects involving image, text, or video data.

What cities in West Virginia are hiring for Senior Data Annotation Analyst jobs?

Cities in West Virginia with the most Senior Data Annotation Analyst job openings:

$77K - $97K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 2 days ago

New


Job description

About the Opportunity

Job Summary

Under the supervision of the Data Quality & Research Administration Analytics Manager and with support of senior level team members, the Senior Data Analyst will work closely with key stakeholders to identify and conduct data analysis projects that support the mission and goals of the University and Northeastern University Research Enterprise Services (NU-RES). The Senior Data Analyst will provide support to key projects through data collection, computational support, and data interpretation and reporting, and will ensure data accuracy and consistent reporting by designing and creating optimal processes and procedures to systematize the data reporting process. The incumbent will use advanced data modeling, predictive modeling, and analytical techniques to develop reports used in key data submissions to internal and external stakeholders. Possess a good sense of humor, ability to be calm under pressure, and effectively communicate with report requestors to ascertain requirements for reports that tell an accurate story.

This position can also reside in Toronto. If you are a Canadian applicant, please submit your application here

Minimum Qualifications

  • Bachelor's Degree in a relevant subject area (e.g., computer science, data science, mathematics, statistics, information technology, or related field); 3+ years of experience with querying databases, SQL, and Microsoft Excel; experience developing robust dashboards using Tableau and/or Power BI; creating visuals using data visualization best practices.
  • Proficiency with business intelligence and reporting tools such as Cognos or Snowflake preferred.
  • Understanding of, and experience in, using analytical concepts and tools, including data modeling and predictive analytics.
  • Project management, time management, and communication skills necessary to execute responsibilities in a collaborative, academic setting.
  • Teamwork and collaboration in a professional setting.
  • Demonstrated curiosity, problem-solving skills, and ability to meet deadlines.
  • Excellent written and oral communication skills with ability to advise and clearly communicate ideas and results to non-technical audiences.
  • Strong ability to manage multiple assignments while working in a fast-paced, deadline-driven environment.
  • Ability to maintain a positive attitude and work well independently, within a team environment, and with external users as well as a variety of internal audiences.
  • Experience working with university research administration data and systems preferred.
  • Experience documenting business procedures and processes preferred.
  • Understanding of, and experience in, using AI-enabled tools to provide appropriate levels of support to daily work.
  • Familiarity with electronic research administration (eRA) systems (e.g., Coeus, ePAWS, or similar eRA platforms) preferred.

Key Responsibilities & Accountabilities

45% - Data Collection, Assessment, Interpretation, and Reporting

Collect relevant data (both internal and external) to be used by college constituents to support decision making and strategic direction, resource allocation, internal and external reporting, and other operational decisions. Success factors include the accuracy and relevance of the data, analysis, and the clarity and usefulness of final reports. Develop and iterate on self-service reports and dashboards with an eye towards automation and re-use. Manage data sourced from both legacy systems (e.g., Coeus) and current eRA platforms (e.g., ePAWS 2.0), ensuring continuity and accuracy across reporting environments.

25% - Data Visualization

Oversee the development and maintenance of key performance dashboards that show progress toward strategic and operational goals related to research. Work closely with Research Enterprise Services stakeholders to identify opportunities for additional dashboard requirements as needs evolve. Develop and iterate on self-service reports and dashboards with an eye towards automation and re-use. Tools include Tableau (including Tableau Prep and Tableau Server), Cognos, and other visualization platforms as applicable.

10% - System Support

Evaluate and test back-end changes to electronic research administration systems as they impact data quality and access, including connectivity with Tableau and the Cognos Data Warehouse environment. Monitor data quality in reports and adjust as needed. Support migration activities between legacy and current systems, including data validation and reconciliation tasks.

10% - Process Improvement

Identify opportunities to define areas for process improvement and work with stakeholders to design and build technical processes that improve efficiencies and address business issues and needs. Develop and maintain documentation of data pipelines, reporting logic, and source-of-truth definitions to support team continuity and institutional knowledge.

10% - Ad Hoc Duties

Perform ad hoc research and analysis to support special projects and strategic initiatives serving faculty and staff across Research Enterprise Services in meeting their reporting and analytical needs. May include supporting AI-assisted data extraction, research analytics benchmarking, and cross-institutional data collaborations.

Applicants must have current work authorization for the country in which they will be based. The University is unable to sponsor a visa or work permit for this position.

Position Type

Data Planning and Analysis

Additional Information

Northeastern University considers factors such as candidate work experience, education and skills when extending an offer.

Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation. Visit https://hr.northeastern.edu/benefits/ for more information.

All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law.

Compensation Grade/Pay Type:

110S

Expected Hiring Range:

$76,335.00 - $107,823.75

With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly-situated employees already in the role. Salary ranges are reviewed regularly and are subject to change.