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Data Scientist Machine Learning Jobs in Kansas (NOW HIRING)

Nuvative Inc

Data Scientist

Wichita, KS · On-site

A Data Scientist at Nuvative, Inc. will have a strong background in data analysis, statistical modeling, and machine learning, with a passion for leveraging data to drive business decisions. As a ...

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Nuvative Inc

Data Scientist

Wichita, KS · On-site

A Data Scientist at Nuvative, Inc. will have a strong background in data analysis, statistical modeling, and machine learning, with a passion for leveraging data to drive business decisions. As a ...

New

Knowmadics

Data Scientist

Wichita, KS · On-site

Develop and evaluate machine learning solutions to interdisciplinary problems in cybersecurity and ... data science experience may also be considered. * 2+ years professional experience with an open ...

StackAdapt

Want to learn more about our Data Science Team: Learn more about our team culture here: Watch our ... Lead the creation and optimization of advanced machine learning algorithms-from developing new ...

Ascend Learning

Sr Data Scientist

Leawood, KS · On-site +1

Design and implement statistical models, anomaly detection algorithms, and machine learning ... Bachelor's degree in Data Science, Statistics, Applied Mathematics, Computer Science, Educational ...

TAMKO

Manufacturing Data Scientist

Phillipsburg, KS

As a Manufacturing Data Scientist at TAMKO, you will be integral to executing the AI and data ... Develop and deploy machine learning, predictive analytics, and prescriptive analytics, including ...

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Amgen

$78K - $107K/yr

Machine Learning Scientist What you will do Let'sdo this.Let'schange the world.Within Amgen ... Experienceworking with biological data, andin applying machine learning to computational biology

Varsity Tutors

Machine Learning Tutor

Overland Park, KS · Remote

$18 - $40/hr

... preparing students for data science roles and advanced AI coursework. * Conceptual Teaching ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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Data Scientist Machine Learning information

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$33.4K

$109.5K

$175.2K

How much do data scientist machine learning jobs pay per year?

As of Jul 13, 2026, the average yearly pay for data scientist machine learning in Kansas is $109,464.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $121,300.00 per year, depending on experience, location, and employer.

What is a Data Scientist Machine Learning job?

A Data Scientist specializing in Machine Learning (ML) uses statistical methods, algorithms, and computational power to analyze data and create predictive models. They work with large datasets to identify patterns, train machine learning models, and improve decision-making processes. Responsibilities often include data cleaning, feature engineering, model selection, and performance evaluation. They may collaborate with engineers and business teams to deploy models in real-world applications. Strong skills in programming (Python, R), ML frameworks (TensorFlow, Scikit-learn), and data visualization are essential.

What are the key skills and qualifications needed to thrive in the Data Scientist Machine Learning position, and why are they important?

To excel as a Data Scientist Machine Learning, you need a strong proficiency in statistics, programming (typically Python or R), and a solid understanding of machine learning algorithms, usually backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as TensorFlow, scikit-learn, SQL databases, and cloud platforms, as well as certifications in data science or machine learning, is commonly expected. Analytical thinking, problem-solving skills, and effective communication are vital soft skills in this profession. These qualifications combine to drive impactful insights and enable the successful development and deployment of machine learning models in business environments.

Is 40 too late for data science?

Data scientists can enter the field at any age, including 40 or older, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and machine learning tools. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and while AI automation tools can assist with certain tasks, MLEs are essential for creating and maintaining complex systems. AI is a tool that enhances their work but does not replace the need for skilled professionals who understand data, algorithms, and system integration.

Which 5 jobs will survive AI?

Data Scientist Machine Learning roles are likely to persist as they require complex problem-solving, domain expertise, and the ability to interpret and communicate insights from data. Jobs that involve creativity, emotional intelligence, and strategic decision-making, such as healthcare professionals, educators, and skilled trades, are also expected to remain resilient despite AI advancements.

What are the typical day-to-day responsibilities of a Data Scientist Machine Learning?

On a typical day, a Data Scientist specializing in Machine Learning might gather and preprocess data, design and implement machine learning models, and evaluate their performance to solve real-world problems. They often collaborate with data engineers, software developers, and business stakeholders to translate business objectives into technical solutions and integrate models into existing systems. Other responsibilities can include visualizing data insights, conducting experiments to tune algorithms, and staying current with new developments in the field. The work is highly collaborative and iterative, requiring clear communication with various teams to ensure project goals are met efficiently.

Do data scientists do machine learning?

Yes, data scientists often use machine learning techniques to analyze data, build predictive models, and extract insights. Proficiency in programming languages like Python or R and understanding of algorithms are essential skills for applying machine learning in their work.
What are the most commonly searched types of Data Scientist Machine Learning jobs in Kansas? The most popular types of Data Scientist Machine Learning jobs in Kansas are:
What are popular job titles related to Data Scientist Machine Learning jobs in Kansas? For Data Scientist Machine Learning jobs in Kansas, the most frequently searched job titles are:
What job categories do people searching Data Scientist Machine Learning jobs in Kansas look for? The top searched job categories for Data Scientist Machine Learning jobs in Kansas are:
Data Scientist Machine Learning jobs near you
Infographic showing various Data Scientist Machine Learning job openings in Kansas as of July 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $109,464 per year, or $52.6 per hour.
Senior Data Scientist

Senior Data Scientist

Garmin International, Inc.

Olathe, KS • On-site

Full-time

Re-posted 27 days ago

Garmin rating

8.8

Company rating: 8.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

9th of 142 rated electronics manufacturers

Job description

Overview
We are seeking a full-time Senior Data Scientist at Garmin's U.S. headquarters in the Greater Kansas City area. In this role, you will be responsible for providing technical leadership and strategic project planning for data science initiatives related to new products, applications, or systems within the company. This role involves leveraging advanced data science techniques to drive innovation and deliver actionable insights that support business objectives. The Senior Data Scientist will collaborate with cross-functional teams, mentor junior data scientists and/or software engineers, and ensure the successful implementation and integration of data-driven solutions.
Essential Functions
  • Lead the design, development, and deployment of advanced AI/ML models and algorithms to solve complex business problems
  • Develop and integrate the AI agents/solutions seamlessly with existing Contract Management Systems (CMS) and document repositories.
  • Lead the design and implementation of end-to-end Retrieval-Augmented Generation (RAG) pipelines to ground LLMs with up-to-date and authoritative external data.
  • Manage the entire data flow for RAG, including document chunking, metadata management, and generating high-quality vector embeddings using state-of-the-art embedding models.
  • Evaluate, select, and manage vector databases (e.g., Pinecone, Weaviate, Qdrant) and indexing techniques (e.g., HNSW) to ensure fast and accurate semantic search and retrieval.
  • Continuously iterate on the RAG components, including retrieval algorithms and prompt engineering strategies, to maximize the contextual relevance and quality of generated responses.
  • Provide technical leadership and mentorship to junior data scientists, fostering a culture of continuous learning and improvement
  • Drive the strategic planning and execution of data science projects, ensuring alignment with business goals and timelines
  • Collaborate with cross-functional teams, including engineering, legal, product management and business stakeholders, to define project requirements and deliver data-driven solutions
  • Develop and implement scalable data pipelines and workflows to support the end-to-end data science lifecycle
  • Evaluate and integrate new data science techniques, tools, and technologies to enhance the company's data capabilities
  • Communicate complex analytical concepts and results to non-technical stakeholders through clear and compelling data visualizations and presentations
  • Ensure the robustness, scalability, and performance of deployed models, monitoring their impact and iterating as necessary
  • Champion best practices in data science, including data governance, model validation, and ethical AI considerations
  • Identify and prioritize opportunities for leveraging data to drive business growth and operational efficiency
  • Lead the development of custom machine learning models and algorithms tailored to specific business needs
  • Stay current with the latest advancements in data science, machine learning, and AI including LLMs, RAG frameworks (e.g., LangChain, LlamaIndex), and vector database technologies, and apply this knowledge to drive innovation within the company
  • Own team-level success by monitoring, modifying and creating team processes to help ensure consistency, continuity, efficiency and impact in analysis and ML pipelines
  • Mentor and guide junior team members, sharing best practices and providing constructive feedback
  • Pioneer peer reviews and foster a culture of continuous improvement and learning
  • Develop and enforce data governance policies and procedures to ensure data integrity and security
  • Monitor compliance with data privacy laws and regulations and implement measures to protect sensitive information

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 5 years of relevant experience OR an equivalent combination of education and relevant experience
  • Excellent academics (cumulative GPA greater than or equal to 3.0 as a general rule)
  • Extensive experience using systems such as SQL, Python, or R
  • Strong expertise in machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch)
  • Proven hands-on experience in fine-tuning Large Language Models (LLMs) and deep understanding of their architectures (e.g., Transformers).
  • Strong experience designing and deploying RAG systems and building high-performance semantic search and retrieval pipelines.
  • Practical experience with vector embeddings and working with vector databases for production-grade applications.
  • Demonstrated 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
  • Advanced experience with structured database management systems and distributed computing
    Expertise in time series analysis, NLP, deep learning, or reinforcement learning
  • Leadership in MLOps, model deployment, and CI/CD for data science workflows
  • Advanced understanding of A/B testing and causal inference
  • Experience working with unstructured data (text, images, audio, etc.)
  • Proficiency with cloud platforms (e.g. AWS, Azure, GCP) for data science workflows
  • Experience with real-time data processing technologies (e.g. Apache, Kafka)

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 Employment Benefits

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