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Intern Data Science Music Jobs in Baltimore, MD (NOW HIRING)

... Intern to join our team. The ideal candidate will play a crucial role in managing and analyzing ... Current undergraduate or graduate student studying public health, data science, social sciences, or ...

2025 Fall Intern, Clinical Applications

Largo, MD · On-site

$14.75 - $19.75/hr

What You Can Expect The Clinical Applications Intern is responsible for providing support to the ... Pursuing a bachelor's degree in Computer Science, Information Systems, Health Informatics, Data ...

2025 Fall Intern, Clinical Applications

Bowie, MD · On-site

$14.50 - $19.50/hr

What You Can Expect The Clinical Applications Intern is responsible for providing support to the ... Pursuing a bachelor's degree in Computer Science, Information Systems, Health Informatics, Data ...

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Intern Data Science Music information

See Baltimore, MD salary details

$11

$22

$41

How much do intern data science music jobs pay per hour?

As of Aug 3, 2026, the average hourly pay for intern data science music in Baltimore, MD is $22.36, according to ZipRecruiter salary data. Most workers in this role earn between $17.21 and $24.38 per hour, depending on experience, location, and employer.

What types of projects can an intern data science music expect to work on, and how do these contribute to the team’s goals?

As an Intern Data Science Music, you can expect to work on projects such as analyzing streaming data to uncover listening trends, building recommendation algorithms, or assisting with the evaluation of audio feature extraction methods. These projects are typically collaborative, allowing you to work closely with data scientists, engineers, and sometimes product managers to deliver actionable insights or prototypes that directly impact how music is discovered and experienced on digital platforms. The work environment is often fast-paced and encourages creative problem-solving, which helps interns gain exposure to real-world data challenges while contributing meaningfully to the team's objectives.

What is the difference between Intern Data Science Music vs Intern Data Analysis Music?

AspectIntern Data Science MusicIntern Data Analysis Music
Required CredentialsBasic programming, statistics, data science fundamentalsStatistics, Excel, basic programming
Work EnvironmentCollaborative teams, research projects, data modelingData review, reporting, visualization tasks
Industry UsageTech, entertainment, music streaming companiesMedia, marketing, music industry firms

Intern Data Science Music and Intern Data Analysis Music roles share foundational skills like statistics and basic programming. However, Data Science internships focus more on developing predictive models and machine learning, while Data Analysis roles emphasize data visualization and reporting. Both are common in the music industry, but Data Science roles often involve more complex data modeling and algorithm development.

What are the key skills and qualifications needed to thrive as an intern in data science for music, and why are they important?

To thrive as an Intern in Data Science for Music, you generally need a foundational understanding of statistics, machine learning, data analysis, and programming skills in languages like Python or R, often supported by coursework or a degree in computer science, statistics, or a related field. Experience with data visualization tools, basic knowledge of audio analysis libraries (such as librosa), and familiarity with SQL or cloud platforms are commonly required. Strong analytical thinking, creativity, and effective communication help you interpret data insights and collaborate with cross-functional teams. These skills are crucial for extracting meaningful patterns from music data, supporting innovation, and driving actionable outcomes in the music industry.

What does an intern data science music do?

An Intern Data Science Music typically assists in analyzing and interpreting music-related data to help improve products or services in the music industry. Their tasks may include collecting and cleaning data, performing statistical analysis, building predictive models, and visualizing musical trends or user behavior. These interns often work with large datasets involving music streaming, song features, or listener preferences, and may collaborate with data scientists, engineers, and product teams. The role offers practical experience in both data science and the unique challenges of the music sector.
What are the most commonly searched types of Data Science Music jobs in Baltimore, MD? The most popular types of Data Science Music jobs in Baltimore, MD are:
What job categories do people searching Intern Data Science Music jobs in Baltimore, MD look for? The top searched job categories for Intern Data Science Music jobs in Baltimore, MD are:
What cities near Baltimore, MD are hiring for Intern Data Science Music jobs? Cities near Baltimore, MD with the most Intern Data Science Music job openings:
Infographic showing various Intern Data Science Music job openings in Baltimore, MD as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 1% Temporary, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $46,511 per year, or $22.4 per hour.

$49K/yr

Other

Re-posted 28 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