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Part Time Spotify Data Science Jobs (NOW HIRING)

DePaul

Adjunct Faculty in Data Science

Chicago, IL · On-site

Adjunct Faculty in Data Science Full-time Faculty Positions Full-time faculty positions will be ... Part-time Faculty Positions DePaul University invites expressions of interest for a pool of ...

Booz Allen Hamilton, Inc.

Data Scientist

Alexandria, VA · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist

Alexandria, VA · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist, Senior

Mclean, VA · On-site

$99K - $225K/yr

On our team, you'll use your leadership skills and data science expertise to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist

Fayetteville, NC · On-site

$99K - $225K/yr

On our team, you'll use your leadership skills and data science expertise to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

Booz Allen Hamilton, Inc.

Data Scientist, Mid

Honolulu, HI · On-site

$77K - $176K/yr

On our team, you'll use your leadership skills and data science expertise to create real-world ... Full-time and part-time employees working at least 20 hours a week on a regular basis are eligible ...

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All JobsPart Time Spotify Data Science Jobs

Part Time Spotify Data Science information

How hard is it to get hired at Spotify?

Getting hired as a part-time data scientist at Spotify typically requires a strong background in data analysis, machine learning, and programming skills in tools like Python or R. Candidates often go through multiple interview rounds assessing technical expertise, problem-solving ability, and cultural fit, making the process competitive but achievable with relevant experience and preparation.

How much do Spotify data scientists make?

Spotify data scientists typically earn between $100,000 and $150,000 annually, depending on experience, location, and skill level. Compensation may also include bonuses, stock options, and benefits, with roles often requiring proficiency in data analysis, machine learning, and programming tools like Python or SQL.

Is it possible to work part-time as a data scientist?

Part-time data science roles, including positions at companies like Spotify, are available and often involve flexible schedules, remote work, and project-based assignments. These roles typically require strong analytical skills, proficiency in tools like Python or R, and relevant experience, but they may have different responsibilities and expectations compared to full-time positions.

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 data. Data scientists often focus on the most impactful features or data subsets to optimize model performance and efficiency.

What is the difference between Part Time Spotify Data Science vs Part Time Spotify Data Engineering?

AspectPart Time Spotify Data SciencePart Time Spotify Data Engineering
Required CredentialsDegree in Data Science, Statistics, or related field; experience with machine learning and analytics toolsDegree in Computer Science, Software Engineering, or related; experience with data pipelines and infrastructure
Work EnvironmentAnalyzing data, building models, interpreting insightsDeveloping and maintaining data pipelines, ensuring data flow and storage
Employer & Industry UsageUsed by Spotify for insights, recommendations, and user behavior analysisUsed by Spotify to manage data infrastructure and support data-driven applications

Part Time Spotify Data Science focuses on analyzing data and building models to generate insights, while Part Time Spotify Data Engineering emphasizes developing data pipelines and infrastructure. Both roles are essential in supporting Spotify's data-driven decisions but differ in their core responsibilities and skill sets.

More about Part Time Spotify Data Science jobs
What cities are hiring for Part Time Spotify Data Science jobs? Cities with the most Part Time Spotify Data Science job openings:
What are the most commonly searched types of Spotify Data Science jobs? The most popular types of Spotify Data Science jobs are:
What job categories do people searching Part Time Spotify Data Science jobs look for? The top searched job categories for Part Time Spotify Data Science jobs are:
Part Time Spotify Data Science jobs near you
Infographic showing various Part Time Spotify Data Science job openings in the United States as of June 2026, with employment types broken down into 2% As Needed, 86% Full Time, 8% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.
Lecturer, Data Science (Temporary Employee Pool)

Lecturer, Data Science (Temporary Employee Pool)

University of the Pacific

San Francisco, CA

Part-time

Posted 6 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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