ZipRecruiter

Log In

1

Manager Annotation Jobs in Kansas (NOW HIRING)

Garmin

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 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

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:

previous page

Showing results 21-26

All JobsAnnotation JobsManager Annotation JobsManager Annotation Jobs in Kansas

Manager Annotation information

What is a manager annotation?

Manager Annotation jobs involve overseeing teams responsible for labeling and annotating data, which is critical for training machine learning models. These managers coordinate workflows, ensure quality control, and facilitate communication between annotators and data scientists. They are responsible for setting guidelines, managing deadlines, and addressing any issues that arise during the annotation process. Manager Annotation roles often require a combination of leadership skills and an understanding of data annotation tools and processes.

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

To thrive as a Manager Annotation, you need expertise in data annotation processes, team leadership, and quality assurance, often supported by a relevant degree and experience in data labeling or AI/ML projects. Familiarity with annotation tools (such as Labelbox, Supervisely, or AWS SageMaker Ground Truth), project management software, and sometimes certifications in project management or data science are valuable. Strong communication, problem-solving abilities, and attention to detail help ensure effective team coordination and high-quality data outputs. These skills are crucial for delivering accurate training data, meeting project deadlines, and supporting the success of machine learning initiatives.

What are some common challenges faced by a manager annotation and how can they be addressed?

A Manager Annotation often encounters challenges such as ensuring high-quality data labeling, managing tight project deadlines, and maintaining effective communication across diverse annotation teams. Balancing quality control with efficiency can be demanding, especially when working with large datasets or remote teams. To address these challenges, it is helpful to establish clear annotation guidelines, implement robust quality assurance processes, and foster open communication channels for feedback and support. Regular training and performance reviews also play a key role in maintaining team standards and project consistency.

What is the difference between Manager Annotation vs Data Annotator?

AspectManager AnnotationData Annotator
Required CredentialsHigh school diploma or equivalent; experience in data labeling; leadership skillsHigh school diploma or equivalent; attention to detail; basic computer skills
Work EnvironmentOffice or remote management setting overseeing annotation teamsRemote or on-site data labeling tasks
Employer & Industry UsageTech companies, AI firms, data service providersAI, machine learning, data processing companies

The main difference is that a Manager Annotation oversees annotation teams and manages projects, requiring leadership and management skills, while a Data Annotator performs the actual data labeling work, focusing on accuracy and attention to detail. Managers coordinate workflows, whereas Annotators execute labeling tasks.

What are the most commonly searched types of Annotation jobs in Kansas?

The most popular types of Annotation jobs in Kansas are:

What are popular job titles related to Manager Annotation jobs in Kansas?

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

What job categories do people searching Manager Annotation jobs in Kansas look for?

The top searched job categories for Manager Annotation jobs in Kansas are:

What cities in Kansas are hiring for Manager Annotation jobs?

Cities in Kansas with the most Manager Annotation job openings:

Manager Annotation jobs near you
Infographic showing various Manager Annotation job openings in Kansas as of August 2026, with employment types broken down into 87% Full Time, 11% Part Time, and 2% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Data Scientist 2

Garmin

Olathe, KS • On-site

Other

Posted 4 days ago

Garmin rating

8.8

Company rating: 8.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

14th of 159 rated electronics manufacturers

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

What Garmin employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply