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Data Science Music Jobs in Miami, FL (NOW HIRING)

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Data Science Music information

See Miami, FL salary details

$16.3K

$99.8K

$190.5K

How much do data science music jobs pay per year?

As of Aug 17, 2026, the average yearly pay for data science music in Miami, FL is $99,846.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,580.00 and $143,467.00 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 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 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 most commonly searched types of Data Science Music jobs in Miami, FL?

The most popular types of Data Science Music jobs in Miami, FL are:

What are popular job titles related to Data Science Music jobs in Miami, FL?

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

What job categories do people searching Data Science Music jobs in Miami, FL look for?

The top searched job categories for Data Science Music jobs in Miami, FL are:

Data Science Music jobs near you
Infographic showing various Data Science Music job openings in Miami, FL as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 100% In-person job distribution, with an average salary of $99,846 per year, or $48 per hour.

Senior Data Scientist

Haystack News

Fort Lauderdale, FL • Remote

Full-time

Re-posted yesterday

Job description

Haystack News, the number one destination for news on streaming platforms, is looking for a Sr Data Scientist to join our team. Haystack is trusted by over 30 million viewers and is among the fastest-growing TV news companies in the world.

Join our team at Haystack News as a Senior Data Scientist and become a pivotal force in redefining user experiences through cutting-edge algorithm enhancements. In this role, you'll leverage your advanced statistical analysis, modeling, causal inference, experimental design (A/B testing) and data analytics expertise to drive substantial improvements in user engagement and retention, directly impacting our product's success. This is an exceptional opportunity to showcase your robust problem-solving capabilities and to thrive in a collaborative environment, working alongside a team of passionate professionals dedicated to innovation and excellence. Be part of a dynamic workplace where your contributions make a meaningful difference and help shape the future of news consumption.

MINIMUM QUALIFICATIONS

  • PhD or M.S. in Computer Science, Mathematics, Electrical Engineering, Statistics, Economics or Operations Research with 5+ years of professional experience in data science, machine learning or related quantitative field

  • 3+ years of professional experience with large-scale online ranking/recommender systems (for news feeds, shopping, ads, music, etc).

  • Deep expertise in statistical inference and experimental design: hypothesis testing, power/sample size calculations, variance reduction, etc.

  • Proficiency in causal inference methods to measure product impact.

  • Proven ability to translate offline analysis into product decisions and measurable improvements in online metrics.

  • Fluency in the Python analytics stack (pandas, NumPy), statistical modeling (statsmodels or scikit-learn) and machine learning packages such as LightGBM and XGBoost.

  • Strong experience with SQL (e.g. postgres, snowflake, etc).

PREFERRED QUALIFICATIONS:

  • Experience working on consumer-facing products with millions of users.

  • Hands-on experience with orchestration/transformation tools (e.g. dbt and Airflow).

  • Experience with deep learning and being familiar with tools such as PyTorch or TensorFlow.

  • Hands-on development of products/tools incorporating GenAI, LLMs, RAG, and/or Agents.

RESPONSIBILITIES

  • Build statistical and machine learning models to improve content discovery and user engagement.

  • Work closely with ML engineers to translate models and insights into production systems.

  • Have curiosity and apply analytical skills to dive deep into data to find key insights that would impact the business.

  • Apply causal inference methods to understand the impact of potential product changes.

  • Define and build new ML features using text and multimodal embeddings and GenAI.

  • Validate offline learnings with online outcomes through AB testing. Design, execute, and analyze experiments to prove product change attribution.