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Part Time Python Data Analysis Jobs in Kansas City, MO

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building ...

Showing results 41-60

Part Time Python Data Analysis information

See Kansas City, MO salary details

$12

$57

$84

How much do part time python data analysis jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for part time python data analysis in Kansas City, MO is $57.20, according to ZipRecruiter salary data. Most workers in this role earn between $47.16 and $65.00 per hour, depending on experience, location, and employer.

What is a part-time Python data analyst?

A part-time Python data analyst is a professional who uses Python programming to analyze, interpret, and visualize data, but works fewer hours than a full-time employee. They help organizations make data-driven decisions by cleaning data, running statistical analyses, and creating reports or dashboards, typically on a flexible or reduced schedule. This role is ideal for those seeking work-life balance or looking to supplement their income while utilizing their data analysis skills.

How do part-time Python data analysts typically collaborate with full-time team members to ensure project continuity?

Part-time Python data analysts frequently work alongside full-time data teams by attending regular meetings, using shared project management tools, and maintaining thorough documentation of their work. This collaboration ensures that progress is transparent and that handoffs between analysts are smooth, minimizing disruptions. Communication platforms like Slack or Microsoft Teams are often utilized to keep everyone aligned, and version control systems such as Git help track changes in code and data analyses. Being proactive about updates and asking clarifying questions also helps part-time analysts integrate effectively with the team.

What are the key skills and qualifications needed to thrive as a part-time Python data analyst, and why are they important?

To thrive as a Part Time Python Data Analyst, you need strong analytical skills, proficiency in Python, and a solid understanding of statistics or data science fundamentals, often supported by relevant coursework or a degree. Familiarity with tools like pandas, NumPy, Jupyter notebooks, and basic SQL, as well as experience with data visualization libraries such as matplotlib or seaborn, is typically required. Attention to detail, problem-solving ability, and effective communication help you convey insights and collaborate with team members. These skills are crucial for extracting meaningful information from data and supporting informed decision-making in a flexible, part-time capacity.

What is the difference between Part Time Python Data Analysis vs Part Time Data Scientist?

AspectPart Time Python Data AnalysisPart Time Data Scientist
Required CredentialsBasic Python, SQL, Excel skillsAdvanced Python, machine learning, statistics
Work EnvironmentData analysis projects, reportingModel development, predictive analytics
Industry UsageBusiness reporting, market researchProduct development, AI applications

Part Time Python Data Analysis typically involves handling data, creating reports, and basic analysis using Python and related tools. In contrast, Part Time Data Scientists work on developing models, applying machine learning, and performing advanced statistical analysis. While both roles require Python skills, Data Scientists usually have more specialized knowledge and work on more complex projects. The choice depends on your skill level and career goals within data roles.

What are the most commonly searched types of Python Data Analysis jobs in Kansas City, MO?

The most popular types of Python Data Analysis jobs in Kansas City, MO are:

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

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

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

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

What cities near Kansas City, MO are hiring for Part Time Python Data Analysis jobs?

Cities near Kansas City, MO with the most Part Time Python Data Analysis job openings:

Infographic showing various Part Time Python Data Analysis job openings in Kansas City, MO as of June 2026, with employment types broken down into 89% Full Time, 9% Part Time, and 2% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $118,985 per year, or $57.2 per hour.

Cheminformatics Specialist - Remote

micro1 AI

Kansas City, MO โ€ข Remote

$80 - $110/hr

Part-time

Posted 19 days ago


Job description

Role Title: Computational Biology & Cheminformatics Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Computational Biology & Cheminformatics Experts to contribute their expertise to a customerโ€™s computational drug discovery project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Analyze and interpret small-molecule and drug discovery datasets using advanced computational biology, bioinformatics, and cheminformatics methods.
  2. Curate, annotate, and validate chemical and biological datasets (e.g., ChEMBL, PubChem, DrugBank) to support AI-driven discovery platforms.
  3. Evaluate compound-target interactions, ADMET properties, and lead optimization strategies by integrating chemical, biological, and clinical data sources.
  4. Provide expert insights on structure-activity and structure-property relationships (SAR/SPR), medicinal chemistry approaches, and experimental design considerations.
  5. Build and implement code-based benchmark tasks (e.g., terminal/CLI-based environments) that reflect realistic computational drug discovery scenarios.
  6. Develop reproducible environments (e.g., using Docker) and automated testing pipelines to ensure task correctness and solvability.
  7. Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance, delivering detailed written feedback and recommendations.


Preferred Qualifications

  1. Advanced expertise in Computational Biology, Cheminformatics, Medicinal Chemistry, Biochemistry, or related fields; advanced degree (PhD, MSc, PharmD) highly valued but not strictly required.
  2. Strong coding proficiency in Python (beyond analysis scripts), with hands-on experience building tools, pipelines, or testable code; familiarity with Git, GitHub, and Docker.
  3. Extensive experience with cheminformatics toolkits and platforms such as RDKit, KNIME, Schrรถdinger, OpenEye, or MOE.
  4. Proven track record in small-molecule drug discovery, SAR/QSAR evaluation, ADMET prediction, or virtual screening workflows.
  5. Comfort working with public chemical and bioactivity databases and integrating diverse datasets for scientific analysis.
  6. Demonstrated ability to clearly communicate complex chemical and biological concepts in written feedback and reports.
  7. Experience participating in multidisciplinary and/or remote projects; familiarity with AI-assisted coding tools is a plus.