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Part Time Data Science Instructor Jobs in Louisiana

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Part Time Data Science Instructor information

See Louisiana salary details

$11.5K

$50.2K

$85.9K

How much do part time data science instructor jobs pay per year?

As of Aug 20, 2026, the average yearly pay for part time data science instructor in Louisiana is $50,208.00, according to ZipRecruiter salary data. Most workers in this role earn between $36,300.00 and $57,300.00 per year, depending on experience, location, and employer.

What does a part time data science instructor do?

A Part Time Data Science Instructor teaches data science concepts and skills to students, typically in a classroom or online setting, on a part-time basis. Their responsibilities include preparing lesson plans, delivering lectures or workshops, guiding students through practical exercises, and providing feedback on assignments. They often cover topics such as statistics, programming (usually Python or R), machine learning, and data analysis. Instructors may also help students with career advice and project-based learning. The part-time nature of the role allows for flexibility and may attract industry professionals who want to share their expertise while maintaining other commitments.

What are some common challenges faced by part time data science instructors, and how can they be addressed?

Part-time data science instructors often juggle teaching responsibilities alongside other professional commitments, which can make time management a challenge. Staying current with rapidly evolving tools and techniques in data science is also essential, as students expect instruction on the latest industry practices. Building engagement and fostering interaction in limited class hours can require creative lesson planning and use of real-world projects. To address these challenges, instructors benefit from leveraging collaborative curriculum resources, actively participating in professional development, and maintaining open communication with students and fellow faculty.

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

To thrive as a Part Time Data Science Instructor, you need a strong background in statistics, programming (commonly Python or R), and data analysis, typically supported by a relevant degree or industry experience. Familiarity with technical tools such as Jupyter Notebooks, machine learning libraries (like scikit-learn or TensorFlow), and data visualization platforms is essential, and teaching certifications can be advantageous. Outstanding communication, adaptability, and the ability to simplify complex concepts help instructors engage and support diverse learners. These skills and qualities are crucial for delivering effective instruction, fostering student understanding, and ensuring positive learning outcomes.

What cities in Louisiana are hiring for Part Time Data Science Instructor jobs?

Cities in Louisiana with the most Part Time Data Science Instructor job openings:

Infographic showing various Part Time Data Science Instructor job openings in Louisiana as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $50,208 per year, or $24.1 per hour.

$49K/yr

Full-time, Part-time

Re-posted 15 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