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Data Annotation Manager Jobs in Houston, TX (NOW HIRING)

CYNET SYSTEMS

Documentum Lead Developer

Houston, TX · On-site

$50 - $55/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Strong understanding of Content lifecycle management, Repository design & security models ... Architect integrations with Brava (document viewing/annotation) and Info Archive (archival strategy ...

CYNET SYSTEMS

Documentum Lead Developer

Houston, TX · On-site

$50 - $55/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Strong understanding of Content lifecycle management, Repository design & security models ... Architect integrations with Brava (document viewing/annotation) and Info Archive (archival strategy ...

New

Hire Up

Nuclear Medicine Technologist

Houston, TX · On-site

Ensure accurate and complete patient documentation and data entry. * Produce high-quality ... Ability to manage multiple priorities in a fast-paced clinical environment. * Strong critical ...

Posted today

MD Anderson

Nuclear Medicine/PET Technologist

Houston, TX

  • Medical

  • Dental

  • Retirement

  • PTO

... management and disposal of radioactive materials. • Uphold MD Anderson's commitment to patient ... privacy and data integrity by following all HIPAA standards. • Travel to off-site imaging ...

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Showing results 21-40

All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Houston, TX

Data Annotation Manager information

See Houston, TX salary details

$29.6K

$92.8K

$164.3K

How much do data annotation manager jobs pay per year?

As of Aug 16, 2026, the average yearly pay for data annotation manager in Houston, TX is $92,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,000.00 and $119,800.00 per year, depending on experience, location, and employer.

What are some common challenges faced by data annotation managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a data annotation manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

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

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Houston, TX?

The most popular types of Data Annotation jobs in Houston, TX are:

What are popular job titles related to Data Annotation Manager jobs in Houston, TX?

For Data Annotation Manager jobs in Houston, TX, the most frequently searched job titles are:

What job categories do people searching Data Annotation Manager jobs in Houston, TX look for?

The top searched job categories for Data Annotation Manager jobs in Houston, TX are:

What cities near Houston, TX are hiring for Data Annotation Manager jobs?

Cities near Houston, TX with the most Data Annotation Manager job openings:

Data Annotation Manager jobs near you

Sr Bioinformatics Software Engineer

Baylor Genetics

Houston, TX • On-site

Full-time

Posted 13 days ago

Baylor Genetics rating

8.4

Company rating: 8.4 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

28th of 120 rated laboratories

Job description

JOB SUMMARY
The Senior Bioinformatics (BI) Software Engineer holds a critical technical role, responsible for designing, developing, and maintaining scalable and efficient software solutions for Baylor Genetics' bioinformatic pipelines. This role involves collaborating with and supporting cross-functional teams to deliver data-driven software solutions aligning with business needs.
KEY RESPONSIBILITIES
  • BI Development:Design, develop, and maintain robust software solutions using various tools, databases, and technologies to meet business requirements.
  • Data Modeling:Create and optimize data models, ensuring the accuracy, integrity, and performance of the underling computational algorithms, especially as pertains to assembly, mapping, variant calling and variant annotation.
  • ETL Processes:Develop and optimize ETL (Extract, Transform, Load) processes to efficiently extract data from various sources, transform it, and load it into the BI system, with an emphasis on utilizing APIs
  • Query Optimization:Analyze and optimize SQL queries and database performance to enhance data retrieval and reporting speed. Contribute to schema design and review sessions to ensure high performance and maintainable databases.
  • Dashboard & Report Creation:Develop interactive dashboards and automated reports using BI tools (e.g., Azure Pipelines, Teams Power Automate, email, Nextflow) to provide actionable insights for stakeholders.
  • Collaboration:Work and align closely with stakeholders, including data analysts, business users, clinical reviewers, laboratory personnel and software developers, to scope their requirements and deliver timely integrations of new software.
  • Data Integration:Integrate disparate data sources and ensure consistency, accuracy, and reliability of data across the BI system, with a focus on devising systems that have minimal to no code debt and are highly maintainable and flexible.
  • Quality Assurance:Conduct rigorous testing of BI solutions to ensure data accuracy, system stability, and optimal performance, with the ability to automate testing suites using packages (e.g. pytest, doctest, Azure Pipelines)
  • Documentation & Maintenance:Create comprehensive documentation for developed solutions and provide support and maintenance as necessary. This generally includes: (1) detailed in-line commenting noting Jira ticket request numbers, genomic diagrams, reasoning and personal thoughts, TODO comments, docstrings, BG headers, etc.; (2) wikis and README files instructing users on how to install and implement the software along with trace mappings detailing how the software is generally organized.

QUALIFICATIONS
Required
  • Education:Bachelor's degree in Computer Science, Software Engineering, Bioinformatics or a related field; Master's degree preferred.
  • Experience:Minimum of 5 years of experience in software development, with a proven track record of designing and implementing scalable software solutions based on diverse user feature needs. Must have a proven track record of implementing production ready software solutions from scratch. Prior experience or domain knowledge from collaborating with laboratory scientists, computational biologists, or clinical reviewers is a nice-to-have.

COMPETENCIES
Technical Skills:
  • Deep knowledge and expertise in at least two programming languages (Python, Perl, R, or Bash, will also consider Java, C++, and Groovy).
  • Proficient in a range of database technologies, including SQL Server, NoSQL, MongoDB, MySQL, and ElasticSearch, demonstrating comprehensive skills in database management, optimization, and query development.
  • Proficiency in working in an Agile framework and implementing CI/CD practices using Git. Knowledge of Azure is a bonus.Implementation of object orientated programming (OOP) is second nature, which includes building intuitive classes relevant to the science, system, or service.
  • Standard software design practices relevant to that language is intuitive to you. Demonstrated ability to build entire software packages from scratch that are performant and highly maintainable, ensuring they are tested and are production ready. Solid understanding and habitual practice of unit and integration testing of software.
  • High regard for documentation and object/variable naming that is explicit, with the ability to relay or distill scientific concepts within supplemental documentation or inline code itself.
  • Proficiency in designing and building APIs and microservices from scratch.
  • Familiarity with Linux OS and HPC clusters (SLURM, Kubernetes, GCP, Azure, etc.) is a plus, but not essential.
  • Solid understanding of package management practices (PIP, Conda, etc.) and containerization (Docker, Singularity, etc.).
  • Proficiency or knowledge of workflow management or orchestration tools (Nextflow, Airflow, Snakemake, etc.) is a plus, but not essential.

Analytical Thinking: Strong analytical and problem-solving skills with the ability to translate complex business needs into technical solutions and work independently to solve problems. Also requires good communication skills and flexibility to reach out to stakeholders and SMEs as necessary
  • Team Collaboration:Excellent interpersonal and communication skills to collaborate effectively with multidisciplinary teams. Should be open and willing to receive and give criticism and feedback in a measured manner, focused on solving the problem at hand.
  • Adaptability:Ability to adapt to evolving technologies, learn new tools, and implement best practices in BI software engineering and development. Should be able to assess situations when a drop-in solution would be preferable to a custom software implementation and run proof-of-concepts as needed. Should be highly familiar with best practices in software development and an advocate of best practices, even under pressure.
  • Project Management:Experience in managing individual projects and adhering to timelines while delivering high-quality solutions, ensuring good communication in situations where project scopes may fluctuate
  • Performs other advanced job-related duties as assigned.

PHYSICAL DEMANDS AND WORK ENVIRONMENT
  • Frequently required to sit.
  • Frequently required to stand.
  • Frequently required to utilize hand and finger dexterity.
  • Frequently required to talk or hear.

EEO STATEMENT
Baylor Genetics is proud to be an equal opportunity employer dedicated to building an inclusive and diverse workforce. We do not discriminate based on race, religion, color, national origin, sex, sexual orientation, age, gender identity, veteran status, disability, genetic information, pregnancy, childbirth, or related medical conditions, or any other status protected under applicable federal, state, or local law.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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