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Part Time Data Analyst R Programming Jobs in Thousand Oaks, CA

... take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

... take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

... take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

... take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

... take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

... take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and ...

M R Walls is a leading innovative architectural wall solution featured in top healthcare, ... Work on cutting-edge AI systems with real operational impact * Part-time or full-time opportunities ...

M|R Walls is a leading innovative architectural wall solution featured in top healthcare, ... Work on cutting-edge AI systems with real operational impact * Part-time or full-time opportunities ...

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Showing results 1-20

Part Time Data Analyst R Programming information

See Thousand Oaks, CA salary details

$35.7K

$86.9K

$142.9K

How much do part time data analyst r programming jobs pay per year?

As of Jun 16, 2026, the average yearly pay for part time data analyst r programming in Thousand Oaks, CA is $86,852.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,700.00 and $101,900.00 per year, depending on experience, location, and employer.

What is the difference between Part Time Data Analyst R Programming vs Part Time Data Analyst Python?

AspectPart Time Data Analyst R ProgrammingPart Time Data Analyst Python
Required SkillsProficiency in R, data visualization, statistical analysisProficiency in Python, data manipulation, machine learning
Work EnvironmentData analysis, reporting, statistical modelingData analysis, automation, machine learning projects
Industry UsageResearch, healthcare, financeTech, finance, marketing

Both roles involve data analysis in a part-time setting but differ mainly in programming language expertise. R is favored for statistical analysis and visualization, while Python is preferred for automation and machine learning tasks. Your choice depends on the specific tools and industry focus.

What job categories do people searching Part Time Data Analyst R Programming jobs in Thousand Oaks, CA look for? The top searched job categories for Part Time Data Analyst R Programming jobs in Thousand Oaks, CA are:
What cities near Thousand Oaks, CA are hiring for Part Time Data Analyst R Programming jobs? Cities near Thousand Oaks, CA with the most Part Time Data Analyst R Programming job openings:
Infographic showing various Part Time Data Analyst R Programming job openings in Thousand Oaks, CA as of June 2026, with employment types broken down into 85% Full Time, and 15% Part Time. Highlights an 80% Physical, 9% Hybrid, and 11% Remote job distribution, with an average salary of $86,852 per year, or $41.8 per hour.
Adjunct Instructor in Data Management, Integration, and Applied Analytics

Adjunct Instructor in Data Management, Integration, and Applied Analytics

Brandeis University

Brandeis, CA

$6.5K/mo

Part-time

Posted 22 days ago


Job description

Brandeis University's Online Information Technology Management Program is seeking an Adjunct Faculty member for RITM 125 Data Management, Integration, and Applied Analytics for the Fall-2 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Information Technology Management.

This course focuses on enterprise data lifecycle management, data modeling, integration workflows, and applied analytics. Students work with data from multiple sources to design structures and processes that support decision-making, quality, and accessibility.

Core Course Responsibilities Summary

  • Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.

  • Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.

  • Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.

  • Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.

Qualifications:

  • Required:

    • Master's degree in Data Science, Information Systems, Computer Science, Data Engineering, Business Analytics, or a closely related field

    • Minimum 3 years of professional experience in enterprise data management, data integration, analytics, or data architecture

    • Demonstrated expertise in data modeling, database design (SQL and NoSQL), ETL/ELT workflows, and data lifecycle management

    • Experience working with analytics tools or programming languages used in applied analytics (e.g., Python, R, SQL, Power BI, Tableau)

    • Minimum 1 year experience developing asynchronous online courses for adult learners in higher education

    • At least 1 year of teaching or training experience (preferably online/asynchronous)

    • Experience with online instruction

    • Excellent communication and teaching skills in an online learning environment.

  • Preferred:

    • Doctorate (PhD or DBA) in Data Science, Information Systems, Computer Science, Analytics, or related field

    • 5+ years of experience in data architecture, enterprise analytics strategy, data governance, or business intelligence leadership

    • Professional experience as a Data Architect, Data Engineer, Analytics Director, BI Lead, or Enterprise Data Strategist

    • Experience with enterprise data governance frameworks and data quality management practices

    • Industry certifications such as Certified Data Management Professional (CDMP), AWS Data Analytics, Azure Data Engineer Associate, Google Professional Data Engineer, or equivalent

    • Prior online teaching experience at the graduate level

    • Knowledge of global learner personas and culturally responsive pedagogy

    • Familiarity with Moodle LMS and digital authoring tools (e.g., H5P)

Interested candidates should submit:

A cover letter highlighting relevant qualifications and teaching experience.

A current CV or resume.

Contact information for three professional references.

Application review begins June 1, 2026 though we will continue to accept submissions on an ongoing basis.

This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.

Compensation for this positon is: $6573.15

Pay Range Disclosure

The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.

Equal Opportunity Statement

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").