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Data Annotation Manager Jobs in Kansas City, KS (NOW HIRING)

Garmin International, Inc.

Data Scientist 2

Olathe, KS · On-site

Design and deploy data pipelines for annotation, training and evaluation, and automate workflows to ... Experience with structured database management systems * Experience with applying statistical ...

Garmin Ltd.

Data Scientist 2

Olathe, KS · On-site

$110 - $160/hr

Design and deploy data pipelines for annotation, training and evaluation, and automate workflows to ... Experience with structured database management systems * Experience with applying statistical ...

EN Engineering LLC

Mechanical Designer

Olathe, KS · Remote

Gather field notes, survey data, design information, vendor information and engineering schematics ... Add annotation and dimensions to plot plans, details, and schematics * Utilize 3D modeling software ...

EN Engineering LLC

Structural Designer

Olathe, KS · Remote

Add annotation and dimensions to foundation location plans, sections, and details to PDF for review ... Ability to self-manage workload and supervise a small design team to execute results * Organization:

All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Kansas City, KS

Data Annotation Manager information

See Kansas City, KS salary details

$29.9K

$93.7K

$165.9K

How much do data annotation manager jobs pay per year?

As of Aug 25, 2026, the average yearly pay for data annotation manager in Kansas City, KS is $93,695.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,700.00 and $121,000.00 per year, depending on experience, location, and employer.

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 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 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 Kansas City, KS?

The most popular types of Data Annotation jobs in Kansas City, KS are:

What are popular job titles related to Data Annotation Manager jobs in Kansas City, KS?

For Data Annotation Manager jobs in Kansas City, KS, the most frequently searched job titles are:

What job categories do people searching Data Annotation Manager jobs in Kansas City, KS look for?

The top searched job categories for Data Annotation Manager jobs in Kansas City, KS are:

Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in Kansas City, KS as of August 2026, with employment types broken down into 84% Full Time, 6% Part Time, and 10% Contract. Highlights an 77% In-person, 6% Hybrid, and 17% Remote job distribution, with an average salary of $93,695 per year, or $45 per hour.

Data Scientist 2

Olathe, KS • On-site

Garmin International, Inc.
Electronics and Appliance Stores • 10K+ employees

8.8

Company rating: 8.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

15th of 159 rated electronics manufacturers

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Learn more about Garmin International, Inc.external

Full-time

Re-posted 6 days ago

Job description

Overview
We are seeking a full-time Data Scientist 2 at Garmin's U.S. headquarters in the Greater Kansas City area. In this role, you will be responsible for analyzing complex data sets, developing machine learning models, and collaborating with cross-functional teams to provide actionable insights and AI solutions. In addition, under guidance or with minimal supervision, this role will apply machine learning, statistical analysis, and data engineering techniques to address challenging business problems.
Essential Functions
  • Under guidance or with minimal supervision, lead the collection, cleaning, and preprocessing of large datasets from diverse sources
  • Conduct advanced exploratory data analysis (EDA) to identify trends, patterns, and anomalies that inform modeling efforts
  • Design, implement, and refine predictive models using machine learning and statistical methodologies
  • Collaborate with cross-functional teams to translate data-driven insights into product and strategy recommendations
  • Design and deploy data pipelines for annotation, training and evaluation, and automate workflows to enhance efficiency
  • Explore, evaluate, and experiment with emerging data science techniques, algorithms, and tools to improve model performance
  • Support integration of models into production systems by coordinating with functional and technical teams and monitoring performance post-deployment
  • Assist in developing and maintaining processes and tools to ensure model performance, reliability, and data quality
  • Create and present compelling data visualizations and reports using advanced graphics and visualization tools
  • Identify and leverage both internal and external datasets to drive innovation and support business solutions
  • Contribute to the development of custom machine learning models and algorithms across diverse datasets
  • Apply predictive modeling to improve user experiences, support revenue growth, and enable data-driven insights
  • Support the definition of project scope and business expectations based on data-driven insights
  • Provide mentorship and share best practices with junior team members under the guidance of senior staff
  • Participate in peer reviews and contribute to the continuous improvement of team processes
  • Demonstrate a commitment to ongoing learning of new technologies, frameworks, and methodologies
  • Ensure data quality, adherence to governance standards, and compliance with data privacy and AI-related regulations

Basic Qualifications
  • Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering, Software Engineering, Aerospace Engineering, Math or Physics or a technical field (such as CIS or IT) relevant to the essential functions of this job description AND a minimum of 1 year of relevant experience
  • Experience using systems such as SQL, Python, or R
  • Strong knowledge of machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
  • Demonstrated understanding of advanced descriptive and inferential statistics
  • Demonstrates expert knowledge in data analysis methods and tools
  • Demonstrated strong and effective verbal, written, and interpersonal communication skills
  • Must be team-oriented, possess a positive attitude, and work well with others
  • Driven problem solver with proven success in solving difficult problems
  • Consistently demonstrates quality and effectiveness in work documentation and organization

Desired Qualifications
  • Experience with structured database management systems
  • Experience with applying statistical methods (e.g. time series analysis, NLP, deep learning, or reinforcement learning)
  • Hands-on experience with MLOps, model deployment, and CI/CD for data science workflows
  • Exposure to distributed computing (e.g., Spark, Dask) and NoSQL databases
  • Understanding of A/B testing and causal inference
  • Experience working with unstructured data (text, images, audio, etc.)
  • Familiarity with data visualization tools (i.e. Matplotlib, Seaborn)

Garmin International is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, citizenship, sex, sexual orientation, gender identity, veteran's status, age or disability.
This position is eligible for Garmin's benefit program. Details can be found here: Garmin Benefits

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