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Part Time Data Science Jobs in Columbus, OH (NOW HIRING)

DATA SCIENTIST

Heath, OH · On-site

$49.96K/yr

Mathematics, statistics, computer science, data science or field directly related to the position ... PART-TIME OR UNPAID EXPERIENCE: Credit will be given for appropriate unpaid and or part-time work.

Research Technician 1

Columbus, OH · On-site

$16.50 - $22.50/hr

... data * Contribute to drafting, editing, and finalizing scientific manuscripts for publication ... part-time, temporary position that will end within 1 year of the start date. Work location is in ...

Analyze data generated by validation studies using statistical methods to determine process ... Education in a relevant discipline such as Life Science, Chemical Engineering, Biomedical ...

Analyze data generated by validation studies using statistical methods to determine process ... Education in a relevant discipline such as Life Science, Chemical Engineering, Biomedical ...

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Part Time Data Science information

See Columbus, OH salary details

$8

$44

$107

How much do part time data science jobs pay per hour?

As of May 28, 2026, the average hourly pay for part time data science in Columbus, OH is $44.99, according to ZipRecruiter salary data. Most workers in this role earn between $14.75 and $66.83 per hour, depending on experience, location, and employer.

What Are Part Time Data Science Jobs?

Part-time data science jobs focus on the collection, analysis, and manipulation of data sets. In this role, you can either work for one employer or freelance on a per-project basis. As a data scientist or data analyst, you mine and analyze information. Your duties also include using statistics and math on the data sets to develop algorithms and models that perform specific processes or aid with your employer’s decision-making. Machine learning engineers use data to create algorithms that help computers and machines process information in structured and unstructured environments and make decisions or take actions based on the data.

What are the key skills and qualifications needed to thrive as a Part Time Data Scientist, and why are they important?

To thrive as a Part Time Data Scientist, you need strong analytical skills, statistical knowledge, and proficiency in programming languages like Python or R, often supported by a degree in a quantitative field. Familiarity with data analysis tools, machine learning libraries, and platforms such as SQL, Jupyter, or Tableau is typically required. Effective communication, time management, and problem-solving abilities help you deliver impactful insights within limited hours. These skills ensure you can efficiently analyze data, present findings clearly, and drive value for organizations even with part-time commitment.

How do part-time data science roles typically structure team collaboration and project ownership?

In part-time data science positions, collaboration is often facilitated through regular virtual meetings, shared project management tools, and clear documentation. Part-time data scientists usually work on specific projects or components, such as data cleaning, exploratory analysis, or building models, while maintaining close communication with full-time team members and stakeholders. This structure allows for flexibility but also requires strong self-management and proactive updates to ensure alignment with the broader team's objectives. Many organizations use agile methodologies to assign tasks and track progress, making it easier for part-time contributors to integrate their work seamlessly.

What is a part-time data science job?

A part-time data science job involves working fewer hours than a full-time data scientist, typically less than 40 hours per week. Part-time data scientists perform many of the same tasks as their full-time counterparts, such as analyzing data, building models, and generating insights to help organizations make data-driven decisions. These roles are ideal for students, professionals seeking additional income, or those looking for flexible work arrangements. Part-time positions may be project-based or ongoing, and can be found in various industries including tech, healthcare, finance, and retail.
What are the most commonly searched types of Data Science jobs in Columbus, OH? The most popular types of Data Science jobs in Columbus, OH are:
What are popular job titles related to Part Time Data Science jobs in Columbus, OH? For Part Time Data Science jobs in Columbus, OH, the most frequently searched job titles are:
What job categories do people searching Part Time Data Science jobs in Columbus, OH look for? The top searched job categories for Part Time Data Science jobs in Columbus, OH are:
What cities near Columbus, OH are hiring for Part Time Data Science jobs? Cities near Columbus, OH with the most Part Time Data Science job openings:
Infographic showing various Part Time Data Science job openings in Columbus, OH as of May 2026, with employment types broken down into 84% Full Time, 12% Part Time, and 4% Contract. Highlights an 75% Physical, 6% Hybrid, and 19% Remote job distribution, with an average salary of $93,576 per year, or $45 per hour.
DATA SCIENTIST

$49.96K/yr

Other

Posted 20 days ago


Job description

The PALACE Acquire Program offers you a permanent position upon completion of your formal training plan. As a Palace Acquire Intern you will experience both personal and professional growth while dealing effectively and ethically with change, complexity, and problem solving. The program offers a 3-year formal training plan with yearly salary increases. Promotions and salary increases are based upon your successful performance and supervisory approval.Qualifications:BASIC REQUIREMENT OR INDIVIDUAL OCCUPATIONAL REQUIREMENT:
Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
You may qualify if you meet one of the following:
1. GS-7: You must have completed or will complete a 4-year course of study leading to a bachelor's from an accredited institution AND must have documented Superior Academic Achievement (SAA) at the undergraduate level in the following:
a) Grade Point Average 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum.
2. GS-9: You must have completed 2 years of progressively higher-level graduate education leading to a master's degree or equivalent graduate degree:
a) Grade Point Average - 2.95 or higher out of a possible 4.0 as recorded on your official transcript or as computed based on 4 years of education or as computed based on courses completed during the final 2 years of curriculum; OR 3.45 or higher out of a possible 4.0 based on the average of the required courses completed in your major field or the required courses in your major field completed during the final 2 years of your curriculum. If more than 10 percent of total undergraduate credit hours are non-graded, i.e. pass/fail, CLEP, CCAF, DANTES, military credit, etc. you cannot qualify based on GPA.
KNOWLEDGE, SKILLS AND ABILITIES (KSAs): Your qualifications will be evaluated on the basis of your level of knowledge, skills, abilities and/or competencies in the following areas:
1. Professional knowledge of basic principles, concepts, and practices of data science to apply scientific methods and techniques to analyze systems, processes, and/or operational problems and procedures.
2. Knowledge of mathematics and analysis to perform minor phases of a larger assignment and prepare reports, documentation, and correspondence to communicate factual and procedural information clearly.
3. Skill in applying basic principles, concepts, and practices of the occupation sufficient to perform routine to difficult but well precedented assignments in data science analysis.
4. Ability to analyze, interpret, and apply data science rules and procedures in a variety of situations and recommend solutions to senior analysts.
5. Ability to analyze problems to identify significant factors, gather pertinent data, and recognize solutions.
6. Ability to plan and organize work and confer with co-workers effectively.
PART-TIME OR UNPAID EXPERIENCE: Credit will be given for appropriate unpaid and or part-time work. You must clearly identify the duties and responsibilities in each position held and the total number of hours per week.
VOLUNTEER WORK EXPERIENCE: Refers to paid and unpaid experience, including volunteer work done through National Service Programs (i.e., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community; student and social). Volunteer work helps build critical competencies, knowledge and skills that can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.Education:IF USING EDUCATION TO QUALIFY: If position has a positive degree requirement or education forms the basis for qualifications, you MUST submit transcriptswith the application. Official transcripts are not required at the time of application; however, if position has a positive degree requirement, qualifying based on education alone or in combination with experience, transcripts must be verified prior to appointment. An accrediting institution recognized by the U.S. Department of Education must accredit education. Click here to check accreditation.
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.Employment Type: OTHER