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Internship Data Science Music Jobs (NOW HIRING)

Melotech

Data Science, Music & Audio

New York, NY · On-site

What you will do Join us as our first dedicated Data Scientist to bring order to the chaos of ... music, video or social media What makes this exciting You are one of the first employees of an ...

Athena LLC

Interns leave with a strong understanding of industry-standard data science practices and potential references for your career.

Cypress HCM

Data Science Engineer

Austin, TX · Hybrid

$65 - $69.72/hr

Data Science Engineer Job Details * Data Science Engineer (Contract) * Location: Austin TX, 78758 ... This role is not suitable for entry-level candidates or interns. Compensation: * $65.00 to $69.72 ...

Evolver

Applied Data Science Intern

Palo Alto, CA · On-site

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In ...

Faire

Data Science Intern

San Francisco, CA

$75/hr

Data Science Internship - Fall 2026 Faire leverages machine learning and data insights to transform the wholesale industry, giving independent retailers the tools to compete with large-scale e ...

Evolver

Applied Data Science Intern

Palo Alto, CA

Applied Data Science Summer Internship About Us: Evolver is a rapidly growing enterprise AI company building advanced solutions for Fortune 500 organizations across finance, tax, risk, and audit. In ...

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

As of Jul 15, 2026, the average hourly pay for internship data science music in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is an internship in data science for the music industry?

An internship in data science for the music industry is a temporary position where students or recent graduates work with music companies or organizations to apply data analysis techniques to music-related problems. Interns may analyze streaming data, build recommendation systems, or help understand listener behavior using machine learning and statistical methods. The goal is to gain practical experience in both data science and the unique challenges of the music sector. These internships often involve working with large datasets, coding, and presenting insights to stakeholders. They can be a great way to start a career at the intersection of technology and music.

What types of projects can I expect to work on during a Data Science internship in the music industry?

As a Data Science intern in the music industry, you’ll typically work on projects involving the analysis of streaming data, user behavior, and recommendation systems. You may assist with developing tools to predict song popularity, analyze listening habits, segment user audiences, or help refine algorithms that personalize playlists. These projects often require collaboration with product managers, engineers, and music curators, offering valuable exposure to both technical and creative problem-solving in a fast-paced, data-driven environment.

What are the key skills and qualifications needed to thrive as an Internship Data Science Music, and why are they important?

To thrive as a Data Science Music Intern, you need foundational knowledge in statistics, programming (Python or R), and basic understanding of music theory or audio analysis, often supported by ongoing studies in data science, computer science, or a related field. Familiarity with data analysis tools like Pandas, NumPy, Jupyter, and music-specific libraries such as librosa, as well as experience with SQL and Git, is highly valued. Strong problem-solving skills, creativity, and effective communication help interns collaborate on innovative projects and present complex findings clearly. These abilities are essential for extracting insights from music data, contributing to team goals, and advancing both technical and creative aspects of music data projects.

What is the difference between Internship Data Science Music vs Data Analyst Music?

AspectInternship Data Science MusicData Analyst Music
Required CredentialsRelevant coursework, basic programming skillsBachelor's in Data Science, Statistics, or related field
Work EnvironmentInternship setting, entry-level projectsFull-time or part-time roles in music industry companies
Industry UsageUsed for training and skill development in music techAnalyzing music consumption, sales, and trends
Search & Comparison IntentUnderstanding internship opportunities in music data scienceComparing roles for career progression in music data analysis

Internship Data Science Music typically involves entry-level training and project work in music-related data science, often as a temporary position. Data Analyst Music is a full-time role focused on analyzing music industry data to inform business decisions. While both roles require analytical skills, internships are more about learning, whereas data analyst positions involve ongoing responsibilities in the music industry.

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What job categories do people searching Internship Data Science Music jobs look for? The top searched job categories for Internship Data Science Music jobs are:
Internship Data Science Music jobs near you

Data Science, Music & Audio

Melotech

New York, NY • On-site

Full-time

Posted 6 days ago

Job description

Who we are
Melotech is revolutionizing media and entertainment. We create art through technology for humans to enjoy. In just 24 months, our work has been heard, watched and loved for over 3 billion minutes worldwide.
Founded by entrepreneur and investor Soheil Mirpour, we are backed by top VCs Cherry Ventures, Speedinvest and GFC, alongside world-class angels from firms such as Spotify, Blackstone and KKR.
What you will do
Join us as our first dedicated Data Scientist to bring order to the chaos of culture. You'll extract insights from hard-to-reach data sources to tackle the big questions: What cultural trends are emerging that everyone else is missing? How can we predict virality? And what factors characterize an underserved category? Working fully autonomously alongside our founder and the team, your answers to these questions will directly influence our company's success. On a typical day, your tasks may include:
  • Discovering and exploiting new, untapped data sources through creative scraping techniques
  • Building data processing pipelines from scratch to handle raw, unstructured data
  • Using LLMs and agentic coding tools to accelerate data cleaning and analysis workflows
  • Spinning up EC2 instances for real-time data collection and automated scraping operations
  • Prototyping and deploying ML models on AWS for real-time predictions and content analysis
  • Creating custom dashboards and reports to communicate insights to leadership
  • Analyzing trends, audience behavior, and performance metrics to guide business decisions

Who you are
We look for battle-tested data scientists who understand that real impact comes from turning messy, unstructured data into business-critical insights that drive company direction. You're someone who doesn't just build models, you solve complex business problems by finding creative ways to access hard-to-reach data and translate statistical findings into actionable strategies. Typically, your profile will look like this:
  • Degree in Data Science, Statistics, CS, Physics, Math, or related quantitative/technical field
  • 3+ years of hands-on data science experience in fast-paced business environments across Tier 1 consultancies, Big Tech companies, high-growth start-ups and scale-ups, or media industry leaders
  • Expert-level Python proficiency with standard data science and ML frameworks
  • Experience scraping and acquiring raw data from new sources, building creative solutions to access hard-to-reach datasets beyond standard APIs
  • Extensive hands-on experience with agentic coding tools and LLMs for data workflows
  • Production model deployment experience including infrastructure and monitoring
  • Advanced data visualization skills using standard libraries or Tableau
  • Strong collaboration skills across engineering, product, and business teams
  • You thrive in a fast-paced and performance-oriented environment
  • Colleagues would describe you as hard-working, ambitious and persistent
  • You're obsessed with music, video or social media

What makes this exciting
You are one of the first employees of an ambitious team, changing the world of media and entertainment. Being early means every decision you make shapes our trajectory. You're not a cog in the machine but the captain of your own ship, rewarded for performance and respected for leadership. Flat hierarchies mean that your voice matters, your ideas get implemented, and your impact is immediate.
We pay competitive salaries and make you an owner of the business with equity. We work remotely to give you complete freedom over your life, while meeting regularly around the world for global offsites where we strategize, bond, and push boundaries together.
What the process will look like
We hire on a rolling basis. Earliest starting date is always ASAP.
Once you begin our process, you can progress from start to offer within a week, depending on how quickly you can move through each stage:
  1. Online assessment: Motivational questionnaire and aptitude test - are you made for the job?
  2. Initial interview: 30-minute introductory call - getting to know you
  3. Take-home case study: Real-world project - showcase your skills and working style
  4. Case interview: 90-minute case discussion - present and debate your results with a team member
  5. Founder interview: 90-minute interview with our CEO - going deep on all topics
  6. Team interview: Individual or group interview with other team members - depending on position
  7. Offer, contract signing and onboarding

Note: As we are still in stealth, you will learn more about Melotech as you progress through the stages. By the end of the Founder interview, you will have a full grasp of our business and the details of your role.

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