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Part Time Data Science Jobs in Berkeley, CA (NOW HIRING)

SLB

AI Solutions Architect

Menlo Park, CA · On-site

$228K - $231K/yr

Full-time or part-time: Full-time Job title: AI Solutions Architect Job Location: 640 W California ... Participate in data science, artificial intelligence, machine learning, and industrial analytics ...

Braze

Senior Lead AI Solutions Consultant

San Francisco, CA · On-site

$130K - $195K/yr

We serve as the pre-sales data scientists to scope use cases, establish credibility with enterprise ... In addition to cash compensation, Braze offers full- and part- time employees a comprehensive Total ...

Stantec

Building Science Consultant

San Francisco, CA · On-site

$85K - $119K/yr

... data organization. * Provide drafting and design support for contract documents using AutoCAD and ... Regular full-time and part-time employees (working at least 20 hours per week) have access to ...

IQVIA

MedTech

San Francisco, CA

$45 - $60/hr

We believe in pushing the boundaries of human science and data science to make the biggest impact ... part-time). Dependent on the position offered, incentive plans, bonuses, and/or other forms of ...

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All JobsPart Time Data Science JobsPart Time Data Science Jobs in Berkeley, CA

Part Time Data Science information

See Berkeley, CA salary details

$10

$52

$125

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

As of Jul 6, 2026, the average hourly pay for part time data science in Berkeley, CA is $52.42, according to ZipRecruiter salary data. Most workers in this role earn between $17.18 and $77.87 per hour, depending on experience, location, and employer.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to improve model performance efficiently.

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 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.

Is 40 too late for data science?

Part time data science roles are accessible at any age, including at 40, provided you have relevant skills such as programming, statistics, and experience with tools like Python or R. Many professionals transition into data science later in their careers, and continuous learning through online courses or certifications can enhance your prospects regardless of age.

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.

Will AI replace data scientists?

AI is transforming the role of data scientists by automating routine tasks like data cleaning and basic analysis, but it does not eliminate the need for human expertise in interpreting results, designing models, and making strategic decisions. Data scientists with skills in programming, statistical analysis, and machine learning remain essential for developing and managing AI systems. The profession is evolving to include more focus on complex problem-solving, domain knowledge, and ethical considerations.

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.

Can you work part-time as a data scientist?

Yes, data science is a field that offers part-time opportunities, especially for freelance or contract roles. These positions often require skills in programming, statistics, and tools like Python or R, and may have flexible schedules to accommodate part-time work arrangements.
More about Part Time Data Science jobs
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What are popular job titles related to Part Time Data Science jobs in Berkeley, CA? For Part Time Data Science jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Part Time Data Science jobs in Berkeley, CA look for? The top searched job categories for Part Time Data Science jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Part Time Data Science jobs? Cities near Berkeley, CA with the most Part Time Data Science job openings:
Part Time Data Science jobs near you
Infographic showing various Part Time Data Science job openings in Berkeley, CA as of June 2026, with employment types broken down into 63% Full Time, 36% Part Time, and 1% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $109,034 per year, or $52.4 per hour.
Lecturer, Data Science (Temporary Employee Pool)

Lecturer, Data Science (Temporary Employee Pool)

University of the Pacific

San Francisco, CA

Part-time

Posted 15 days ago

Job description

Position Information
Title Lecturer, Data Science (Temporary Employee Pool) Campus Stockton Department Data Science Posting Number F01077 Full or Part Time Part Time Open Date 05/22/2026 Close Date 12/14/2026 Open Until Filled Yes Days Per Week 3 Weeks Per Year 15
Position Description
Primary Purpose and Essential Functions
The University of the Pacific is seeking a dynamic and data-driven Adjunct Faculty member to lead a specialized, one-unit experiential learning course in Customer Analytics for the Fall 2026 semester.
The School of Engineering and Computer Science at the University of Pacific invites applications for a part-time, non-tenure track Lecturer position in the Data Science Department. We are seeking a lecturer to teach a 1-unit, 15-week asynchronous online course for the Master of Science in Data Science program. The lecturer will be responsible for organizing course content and materials, producing weekly video lectures aligned with the course's learning outcomes, designing and grading weekly assignments, and providing online (office hour) support to students. In addition, the instructor will also create and coordinate project work for the weekly, in-person, 3-hour Data Science Socratic Lab, which provides an interactive support component for students enrolled in asynchronous courses.
We are looking for someone with expertise to teach the following courses:
  • Customer Analytics (fall semester)

University of the Pacific recognizes that diversity, equity, and inclusion is foundational to the success of our valued students and employees. We prioritize policy and decision-making that demonstrates awareness of, and responsiveness to, the ways socio-cultural forces related to race, gender, ability, sexuality, socio-economic status, etc. impede or propel students, faculty, and staff.
Minimum Qualifications
  • Master's or Ph.D. in Data Science, Computer Science, Business Analytics, or a related field
  • Demonstrated experience in retail analytics, e-commerce, or consumer data modeling.
  • A commitment to experiential learning and the ability to translate technical concepts into business value.
Preferred Qualifications
  • Knowledge and experience in data science, specifically customer analytics.
  • Experience and sensitivity in working with people of diverse backgrounds and cultures.
  • Demonstrated experience in advancing social justice, equity, and inclusion in a university setting.
  • Ability to engage and integrate culturally responsive practices and knowledge in their work.
Physical Requirements
Physical Requirements:
The physical demands described here are representative but not definitive of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Requires extended periods of sitting and repetitive hand/wrist motion while using a computer keyboard and phone. Occasional standing, walking, climbing stairs, bending, stooping, and reaching. Occasional lifting of up to 25 pounds.

No Visa Sponsorship:
This position is not eligible for visa sponsorship now or in the future.
Hiring Range $5000.00 per unit (We consider factors such as, but not limited to, scope and responsibilities of the position, candidate's qualifications, internal equity, as well as market and organizational considerations when extending an offer.) Special Instructions
To apply, please submit the following:
  • Curriculum vitae
  • Contact information for three references
Contact Information
Dr. James Hetrick
Professor/Director of Data Science.
email: jhetrick@PACIFIC.EDU
Contact Email jhetrick@pacific.edu
Reference Letter Information
Are Applicants Required to Submit References for This Posting? Yes Minimum Number of References 3 Maximum Number of References 3 Background Check Statement
All applicants who receive a conditional offer of employment are required to execute a release and authorization for a background screening.
AB 810 Misconduct Disclosure Requirement: University of the Pacific complies with California Assembly Bill 810, requiring candidates accepting conditional job offers to disclose any final administrative or judicial findings, ongoing proceedings, allegations, resignations under investigation, or appeals related to sexual harassment or misconduct within the past seven years.
Anti-Discrimination/EEO Policy Statement

University of the Pacific is an equal opportunity employer dedicated to workforce diversity across backgrounds, experiences, and viewpoints. Pacific does not unlawfully discriminate in its hiring of faculty and staff, or in the provision of its employment benefits to its faculty and staff on the basis of race, color, religion, national origin, ancestry, age, genetic information, sex/gender, marital status, military and veteran status, sexual orientation, medical condition, pregnancy, gender identity, gender expression, or mental or physical disability, or other legally protected characteristics or combination of such characteristics. While we strive to attract a broad and representative pool of candidates, all hiring decisions are made based on merit, selecting the most qualified individual for each position.

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