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Freelance Machine Learning Data Annotation Jobs in Lenexa, KS

Data Scientist

Kansas City, KS · On-site

$110 - $160/hr

Experience working in a Data Science, Machine Learning, Applied Statistics or similar role. Proven experience designing, validating and monitoring applied machine learning models. Robust experience ...

New

Data Engineer II

Leawood, KS · On-site

$111K - $133K/yr

Design and optimize data pipelines that support AI, machine learning, and advanced analytics workloads. * Implement data preprocessing, feature engineering, and real-time inference capabilities for ...

Data Engineer III

Leawood, KS · On-site

$111K - $133K/yr

Lead efforts to optimize data pipelines that support AI, machine learning, and advanced analytics workloads. * Implement and productionize feature engineering pipelines, model data pipelines, and ...

Full Lifecycle Data Engineer

Kansas City, MO · On-site

$111K - $134K/yr

... machine learning. Key Responsibilities Data Ingestion & Integration • Build and maintain scalable batch and streaming data pipelines • Integrate data from APIs, event streams, databases, SaaS ...

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

AI Engineer

Kansas City, MO · On-site

$50K - $112K/yr

Responsibilities - Designing and implementing AI systems to transform raw data into actionable insights - Developing scalable machine learning models using Python and TensorFlow - Integrating data ...

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Freelance Machine Learning Data Annotation information

See Lenexa, KS salary details

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How much do freelance machine learning data annotation jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for freelance machine learning data annotation in Lenexa, KS is $20.53, according to ZipRecruiter salary data. Most workers in this role earn between $16.25 and $23.46 per hour, depending on experience, location, and employer.

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Lenexa, KS look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Lenexa, KS are:

What cities near Lenexa, KS are hiring for Freelance Machine Learning Data Annotation jobs?

Cities near Lenexa, KS with the most Freelance Machine Learning Data Annotation job openings:

Infographic showing various Freelance Machine Learning Data Annotation job openings in Lenexa, KS as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 14% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $42,695 per year, or $20.5 per hour.

Data Scientist

NovationIQ

Kansas City, KS • On-site

$110 - $160/hr

Other

Posted yesterday

New


Job description

Job Description Summary

We are seeking a creative and curious individual to join our team as a Data Scientist. In this role, the successful candidate will lead the design, development and validation of advanced models aimed at improving decision-making and supporting an evidence-informed predictive framework. The successful candidate will work closely with coaches, scouts, analysts and other stakeholders, translating complex data into key insights, developing interpretable and context-relevant models across medical, sports sciences, scouting, squad planning and performance analysis, contributing to the development of proprietary models that provide Sporting Kansas City with a sustainable competitive advantage. Sporting Kansas City is an equal opportunity employer. We celebrate diversity and equity and are committed to creating an inclusive environment for all associates. All associates are expected to positively collaborate with individuals of diverse backgrounds. We encourage all talented individuals looking for a challenge to apply.

People

Work closely with coaches, analysts, scouts and other key stakeholders to identify football questions and translate them into advanced modelling projects. Develop strong relationships with the wider Data and Analytics team, ensuring alignment with Club and department strategy. Work very closely with the First Team Data Engineer to ensure advanced modelling is supported by reliable data and production-ready workflows. Collaborate closely with the First Team Data Analyst, ensuring the model outputs are translated and communicated into clear and actionable insights. Ensure collaboration and communication across the wider Club as needed, championing the adoption of advanced analytics across Sporting Kansas City.

Process

Lead the end-to-end development of applied advanced modelling projects, from problem definition with key stakeholders, through to deployment and review cycles. Develop robust tools for testing, validation, versioning, monitoring, model governance and documentation, focusing on creating and establishing best practices for experimentation. Continuously evaluate model performance, incorporating stakeholder feedback to ensure reliability and flexibility as the Club changes and evolves. Evaluate other emerging methods and research to ensure SKC stays current with data science best practice and trends.

Product

Develop advanced models to support medical, sports sciences, scouting, coaching and performance analysis workflows. Support the development of advanced football metrics including player, team, league and valuation models, combining and utilizing multiple data sources. Develop advanced metrics, working extensively with event, tracking and physical data. Support the creation of predictive models related to load monitoring and management, player availability, injury risk and other key projects in collaboration with the medical and physical performance staff. In close alignment with the wider Data and Analytics teams, support the development of forecasting and scenario-analysis tools, supporting squad and salary cap planning. Continuously challenge existing data, systems and practices to ensure development and drive innovation. Work closely with the First Team Data Engineer to productionize models and implement ML projects seamlessly.

Education & Experience

Bachelor's degree in computer science, data science or related STEM subject. Experience working in a Data Science, Machine Learning, Applied Statistics or similar role. Proven experience designing, validating and monitoring applied machine learning models. Robust experience using both SQL and Python for data analysis, modelling and automation. Strong understanding of statistical modelling, experimental design and model evaluation. Creative and curious problem solver with a positive attitude to new challenges. Proactive and keen to learn, able to pick up new skills and work as part of a team. Excellent attention to detail and evidence of working on developing strong analytical skills. Evidence of excellent communication skills, able to translate technical concepts into practical solutions.

Preferred Experience

Prior experience working within an elite soccer club or high-performance sporting environment. Experience working with soccer event, tracking and physical performance datasets. Previous experience developing models for elite athlete recruitment, physical performance, squad planning, player availability and load and fatigue management. Experience deploying machine learning models and working with cloud-based environments. Strong understanding of technical and tactical aspects of soccer. Evidence of experience working in the MLS. Experience using data visualization tools such as Tableau or other equivalent software.

Physical Requirements

Ability to work in office, stadium, and outdoor environments with the ability to travel as required. Ability to occasionally lift up to 25 pounds. Ability to work non-traditional hours including evenings, weekends, and holidays.

Additional Responsibilities

Represent Sporting Kansas City professionally at all times. Maintain confidentiality of sensitive information. Comply with Club policies and procedures. Perform other duties as assigned.

Our Mission

We elevate Kansas City, transform American soccer, and create memories through personalized experiences with our Club. Our promise is to continually delight our fans and set the benchmark for best practices across Major League Soccer.

Our Values

At Sporting Kansas City, we strive to win championships, deliver a world-class product on and off the field, create the finest fan experiences in sports, create meaningful connections with the community, and innovate in all that we do.

Our Passion for Diversity, Equity, & Inclusion

Sporting Kansas City is an equal opportunity employer. We strive to create an empowering environment for a diverse and inclusive team of associates who make a positive impact on our Club and our community. Individuals from all backgrounds are celebrated and encouraged to apply.

Our Championships

MLS Cup Championship: 2000, 2013 Lamar Hunt US Open Cup: 2004, 2012, 2015, 2017 Supporter’s Shield: 2000

Our Ownership

Sporting Kansas City is owned by Sporting Club, an entity comprised of local business and community leaders. Sporting prides itself on a commitment and vision to provide high-performance experiences. Sporting Club purchased the team from the Hunt Sports Group in 2006, and under its direction has launched Swope Soccer Village, Sporting Park, Compass Minerals Sporting Fields, Compass Minerals National Performance Center and Central Bank Sporting Complex while investing in the Sporting KC Academy and Sporting Kansas City II for developing local youth into homegrown talent. Sporting Kansas City is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all associates.

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