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Remote Data Science Music Jobs (NOW HIRING)

Data Science Analyst - Remote

Brentwood, TN ยท On-site +1

$75K - $87K/yr

This is a Full Time, remote, Data Science Analyst role. What You'll Do Data Analysis & Manipulation: * Perform exploratory data analysis to identify patterns and opportunities in healthcare data

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Remote Data Science Music information

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$41.5K

$142.5K

$201K

How much do remote data science music jobs pay per year?

As of Jul 14, 2026, the average yearly pay for remote data science music in the United States is $142,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,500.00 and $166,500.00 per year, depending on experience, location, and employer.

How does a remote data science role in the music industry typically collaborate with other departments, such as marketing or A&R?

In a remote data science music role, collaboration with teams like marketing, product, and A&R (Artists & Repertoire) is often achieved through regular virtual meetings, shared analytics dashboards, and cross-functional project management tools. Data scientists may analyze listener trends, predict song success, or segment audiences, providing actionable insights to guide marketing campaigns and artist development strategies. Strong communication skills and proactive coordination are essential, as data-driven recommendations directly inform creative and business decisions within the company.

What are the key skills and qualifications needed to thrive as a Remote Data Science Music professional, and why are they important?

To thrive as a Remote Data Science Music professional, you need strong skills in statistics, machine learning, and music theory, often supported by a degree in data science, computer science, or music technology. Familiarity with programming languages like Python or R, experience with audio analysis tools, and proficiency in music-specific data platforms are typically required. Creativity, problem-solving, and effective remote communication are crucial soft skills for success in collaborative and innovative projects. These skills enable the effective analysis of music data, drive innovation in music technology, and foster productive teamwork in a remote environment.

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

AspectRemote Data Science MusicRemote Data Analysis
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/R; knowledge of music dataBachelor's in Data Analysis, Statistics, or related; proficiency in Excel, SQL, and visualization tools
Work EnvironmentCollaborative teams, often in tech or entertainment industries, with a focus on music dataBusiness or research settings analyzing various data types, often in finance, marketing, or healthcare
Employer & Industry UsageMusic tech companies, streaming services, entertainment industryCorporate, research institutions, marketing agencies across multiple industries

Remote Data Science Music involves applying data science skills specifically to music-related data, often requiring knowledge of music industry trends and audio data analysis. Remote Data Analysis is broader, focusing on analyzing various data types across industries. While both roles require strong analytical skills and familiarity with data tools, Remote Data Science Music emphasizes music-specific data and industry knowledge.

What is a Remote Data Science Music job?

A Remote Data Science Music job involves using data analysis, machine learning, and statistical techniques to analyze or generate music-related data, all while working remotely. Professionals in this field may work with streaming data, user preferences, music recommendation systems, audio signal analysis, or music composition algorithms. They typically collaborate with music platforms, record labels, or research teams to uncover trends, improve recommendations, or create new music experiences. This role requires both data science skills and an understanding of music theory or the music industry.
More about Remote Data Science Music jobs
What cities are hiring for Remote Data Science Music jobs? Cities with the most Remote Data Science Music job openings:
What are the most commonly searched types of Data Science Music jobs? The most popular types of Data Science Music jobs are:
What states have the most Remote Data Science Music jobs? States with the most job openings for Remote Data Science Music jobs include:

Full-time

Posted 11 days ago


Job description

Data Scientist nlp remote

Data Scientist to help revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

Youll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. Youll collaborate closely with cross-functional teams to:

Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If youre excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

Qualifications

3+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Proficiency with Python
Experience with the latest in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
Bonus Experience

Experience with document layout analysis (using vision, NLP, or both).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
Responsibilities

Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
After 3 Months, You Will

Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
After 1 Year, You Will

Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on models and a source from which other teams can seek information and recommendations.

Data Scientist nlp remote

Data Scientist to help revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

Youll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. Youll collaborate closely with cross-functional teams to:

Design and develop models to extract entities, detect intents, and understand document structure
Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs
Evaluate model performance where ground truth is partial, uncertain, or evolving
Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If youre excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

Qualifications

3+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.
Proficiency with Python
Experience with the latest in language models (transformers, LLMs, etc.)
Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.
Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow
Industry experience shepherding ML/AI projects from ideation to delivery
Demonstrated ability to influence company KPIs with AI
Demonstrated ability to navigate ambiguity
Bonus Experience

Experience with document layout analysis (using vision, NLP, or both).
Experience with Spark/PySpark
Experience with Databricks
Experience in the healthcare industry
Responsibilities

Play a key role in the success of our products by developing models for document understanding tasks.
Perform error analysis, data cleaning, and other related tasks to improve models.
Collaborate with your team by making recommendations for the development roadmap of a capability.
Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.
Understand product use-cases and define key performance metrics for models according to business requirements.
Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).
After 3 Months, You Will

Have a strong grasp of technologies upon which our platform is built.
Be fully integrated into ongoing model development efforts with your team.
After 1 Year, You Will

Be independent in reading literature and doing research to develop models for new and existing products.
Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.
Be a subject matter expert on Datavants models and a source from which other teams can seek information and recommendations.

Working Place:

NYC, New York, United States

Company
:


ESR Healthcare