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Data Science Music Jobs in California (NOW HIRING)

Applied Scientist

Culver City, CA ยท On-site

$150 - $200/hr

... music in spatial audio, worldโ€‘class workouts and meditations, super fun games and more! The Services Data Science & Analytics organization is passionate about developing discerning insights and ...

... music, sports, cooking, and more. It is where thousands of communities come together for whatever ... OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in ...

Machine Learning Scientist

San Francisco, CA ยท On-site

$200 - $250/hr

We are a team of musicians and AI experts, including alumni from Spotify, TikTok, Meta and Kensho ... Intimate familiarity of the entire stack of data engineering, designing, training and evaluating ...

Data Scientist

San Francisco, CA ยท On-site

$157K - $212K/yr

... music, sports, cooking, and more. It is where thousands of communities come together for whatever ... OR a PhD in Economics, Statistics, Computer Science, or related quantitative field * Proficiency in ...

Showing results 21-40

Data Science Music information

See California salary details

$17.1K

$104.9K

$200.3K

How much do data science music jobs pay per year?

As of Sep 7, 2026, the average yearly pay for data science music in California is $104,949.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,961.00 and $150,801.00 per year, depending on experience, location, and employer.

What is a Data Science Music job?

A Data Science Music job involves applying data analysis, machine learning, and statistical techniques to the music industry. Professionals in this field work with streaming data, listener preferences, audio analysis, and recommendation systems to enhance user experiences and optimize business strategies. They may collaborate with music platforms, record labels, or artists to analyze trends, predict hits, and improve content discovery. This role requires proficiency in programming, data visualization, and a deep understanding of both music and data science.

What types of projects do Data Science Music professionals typically work on within a music technology company?

Data Science Music professionals commonly tackle projects such as developing music recommendation algorithms, analyzing trends in streaming data, building audio classification systems, and optimizing playlist curation tools. They may also work on tasks like genre or mood detection, user personalization features, and even acoustic fingerprinting for copyright protection. Collaboration is frequent, often working closely with software engineers, product managers, and musicologists to bring these solutions to life. These projects contribute directly to improving user experience and innovation in digital music platforms, offering a dynamic and intellectually stimulating work environment.

What are the key skills and qualifications needed to thrive in the Data Science Music position, and why are they important?

To thrive in Data Science Music, you need a strong background in statistics, machine learning, and audio signal processing, typically supported by a relevant degree in data science, computer science, or music technology. Familiarity with tools such as Python, R, TensorFlow, and specialized audio analysis libraries (like librosa), as well as experience with music databases and recommendation systems, is essential. Creativity, problem-solving skills, and effective collaboration are valuable soft skills in this interdisciplinary field. These skills are crucial for building data-driven solutions that enhance music analysis, recommendation, and production in the rapidly evolving music industry.

What are popular job titles related to Data Science Music jobs in California?

For Data Science Music jobs in California, the most frequently searched job titles are:

What cities in California are hiring for Data Science Music jobs?

Cities in California with the most Data Science Music job openings:

Infographic showing various Data Science Music job openings in California as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 15% Part Time, and 5% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $104,949 per year, or $50.5 per hour.

Senior Data Scientist, Causal Inference + Experimentation

Jackalope Digital LLC

San Francisco, CA โ€ข On-site

$200 - $250/hr

Other

Posted 15 days ago


Job description

Discord has a highly engaged community of millions of daily active users who use the platform for many different reasons, but thereโ€™s one thing that nearly everyone does: play video games. Discord plays a uniquely important role in the future of gaming, and we are focused on making it easier and more fun for people to hang out before, during, and after playing games.

Discord is looking for an experienced, proactive, and self-driven Senior Data Scientist to join our Experimentation Platform team.The Experimentation Platform puts data at the heart of the companyโ€™s decision-making and growth by enabling rapid and accurate product experimentation. Discord runs hundreds of experiments on any given day, turning experiment results into business decisions. As a Data Scientist on this team, you will ensure that the statistical underpinnings of our experiments are sound, that experimenters are able to design experiments with high rigor, and that Discord makes the best business decisions on the basis of these experiments. We are a small and quickly growing team; you will be presented with significant leadership opportunities as we evolve.

Our team directly impacts the strategy and roadmaps that improve Discord for its more than 90M daily active users! If helping make Discord an even better place to hang out with your friends sounds like an exciting challenge - we'd love to chat with you! Check out our blog about how our team informs strategy & innovation at Discord here!

What Youโ€™ll Be Doing
  • Collaborate closely with engineering and product teams to improve the reliability and scalability of experimentation at Discord.
  • Provide statistical expertise, ensuring that all statistical choices, methodologies, and frameworks are sound and aligned with best practices in causal inference and experimental design.
  • Lead initiatives to educate and train cross-functional teams on best practices in experimentation design, statistical methodologies, and causal inference, ensuring a deep understanding of the principles that drive sound decision-making under uncertainty.
  • Develop and deliver engaging workshops, training sessions, and educational materials that demystify complex statistical concepts and promote data-driven decision-making across the company.
  • Empower our Data Science team (50+ members) to use more rigorous causal inference methods.
  • In addition to consulting within the wider Data Science team (50+ members), lead and conduct causal inference research of your own on important Discord priorities.
What you should have
  • Proven experience in designing and validating statistical methodologies for experimentation platforms or similar systems, with a focus on ensuring the accuracy and reliability of experimental results.
  • MSc in a quantitative field (e.g. Statistics, Economics, Political Science, Psychology, etc.) and 2+ years of experience designing, implementing and analyzing experiments or causal inference projects.
  • Ability to critically evaluate and recommend statistical approaches and methodologies that enhance the integrity of experimentation frameworks.
  • Strong passion for education and the ability to communicate complex statistical and experimental design concepts clearly and effectively to both technical and non-technical audiences.
  • Demonstrated experience in developing and delivering training programs or educational content related to experimentation, causal inference, or statistical analysis, with a track record of fostering a culture of data literacy within an organization.
  • Proficient with Python, SQL, R, and other statistical programming languages.
Bonus Points
  • PhD in a quantitative field
  • Interest in conducting literature reviews, translating and championing best scientific practices to a wide range of functions across the company.
  • Track record in using causal inference methods that translated into business decisions and outcomes.
  • Passion for Discord or gaming.
  • Causal inference related publications.

The US base salary range for this full-time position is $220,500 to $245,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

Why Discord?

Discord plays a uniquely important role in the future of gaming. We're a multiplatform, multigenerational and multiplayer platform that helps people deepen their friendships around games and shared interests, and helps developers build and grow their businesses. We believe games give us a way to have fun with our favorite people, whether listening to music together or grinding in competitive matches for diamond rank. Join us in our mission! Your future is just a click away!

Discord is committed to inclusion and providing reasonable accommodations during the interview process.

Please see our Applicant and Candidate Privacy Policy for details regarding Discordโ€™s collection and usage of personal information relating to the application and recruitment process by clicking HERE.

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