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Python Data Science Jobs in Kansas City, MO (NOW HIRING)

NinjaOne

Senior Data Engineer

Kansas, KS · On-site +1

$93K - $127K/yr

... and data science. * Demonstrated business impact and growth in prior roles * Expertise in Python and SQL. * Experience building ETL pipelines and managing large-scale data systems. * Strong ...

Concord

Decision Scientist

Kansas City, MO · On-site

$80K - $100K/yr

Strong understanding of SQL & Python. * Strong communication skills, verbal and written, and enjoys ... Ability to gather requirements and generate Data Science & Engineering tickets as needed. * Ability ...

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$57

$84

How much do python data science jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for python data science in Kansas City, MO is $57.13, according to ZipRecruiter salary data. Most workers in this role earn between $47.12 and $64.90 per hour, depending on experience, location, and employer.

What is a Python data science?

A Python Data Science job involves using Python to analyze, process, and visualize data to extract insights and inform decision-making. It typically includes working with libraries like Pandas, NumPy, and Scikit-learn for data manipulation, statistical analysis, and machine learning. Professionals in this role may clean and preprocess data, build models, and communicate findings through reports or visualizations. Python Data Scientists often work in industries like finance, healthcare, and technology to solve complex problems and optimize business strategies.

What does a Python data science do?

In a Python Data Science role, your typical day might involve collecting, cleaning, and preparing raw data, exploring datasets to uncover patterns and trends, and building or evaluating predictive models. You’ll regularly use Python libraries to conduct analyses, visualize results, and collaborate with cross-functional teams such as product managers or engineers to define business objectives. Presenting your findings in clear, actionable formats for both technical and non-technical stakeholders is also a key part of the job. This dynamic environment emphasizes continuous learning, problem-solving, and close communication with other departments to align analytical insights with organizational goals.

What are the key skills and qualifications needed to thrive in the Python data science position?

To thrive in Python Data Science, you need strong programming skills in Python, a solid understanding of statistics, data manipulation, and experience with data analytics or machine learning, often supported by a bachelor’s or master’s degree in a quantitative field. Familiarity with tools such as pandas, NumPy, scikit-learn, Jupyter Notebooks, and knowledge of SQL are typically essential; certifications like Google Data Analytics or IBM Data Science can be advantageous. Critical thinking, problem-solving, and effective communication are key soft skills for translating data insights into actionable business recommendations. These skills are crucial to efficiently analyze large datasets, build predictive models, and deliver meaningful insights that drive decision-making.

How much do Python data scientists make?

Python data scientists typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with advanced skills in machine learning and big data tools can earn higher salaries, often exceeding $150,000. Salary levels also vary based on certifications and the complexity of projects handled.

Is Python useful for data science?

Python is a widely used programming language in data science, valued for its simplicity and extensive libraries such as Pandas, NumPy, and scikit-learn. Data scientists and analysts often use Python for data manipulation, analysis, and machine learning tasks, making it a key skill in the field.

Which Python Data Science job is in demand?

Data Scientist and Machine Learning Engineer roles are currently in high demand in Python Data Science, especially those with skills in libraries like Pandas, NumPy, and scikit-learn, and experience with cloud platforms. These positions often require strong analytical skills, programming proficiency, and knowledge of statistical modeling or deep learning.

What are popular job titles related to Python Data Science jobs in Kansas City, MO?

For Python Data Science jobs in Kansas City, MO, the most frequently searched job titles are:

What job categories do people searching Python Data Science jobs in Kansas City, MO look for?

The top searched job categories for Python Data Science jobs in Kansas City, MO are:

Python Data Science jobs near you
Infographic showing various Python Data Science job openings in Kansas City, MO as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $118,985 per year, or $57.2 per hour.

Data Scientist (Statistician) - Direct Hire

Kansas City, MO • On-site

US Department of the Treasury
Public Administration • 10K+ employees
Learn more about US Department of the Treasuryexternal

$125K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Key responsibilities

  • Identify and assess the validity and reliability of relevant data sources and retrieve structured and unstructured data for data science projects.

  • Clean, transform, combine, and integrate data from multiple sources to prepare data for analysis.

  • Apply data-mining process models and statistical methods to analyze data, evaluate results, and support program or business decisions.

U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

Job description

WHAT IS LARGE BUSINESS AND INTERNATIONALDIVISION?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:
  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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