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Remote Data Science Music Jobs in Philadelphia, PA

Soni Resources

Data Scientist

Conshohocken, PA · On-site +1

$175K/yr

... Data Science + Data Engineering) Location: Remote (Preference for Northeast/Mid-Atlantic; monthly travel to Plymouth Meeting, PA as needed) Our client is building a data-driven culture where ...

Eastern University

Adjunct Faculty- Data Science

PA · On-site +1

Remote Optional Job Number: 515 Department: Data Science - (College of Health and Sciences) Opening Date: 01/25/2024 Join our vibrant community of dedicated faculty and staff who work to create a ...

Bread Financial

Lead Data Scientist

Chadds Ford, PA · On-site +1

$138K - $272K/yr

Bachelor's Degree in Statistics, Mathematics, Engineering, Data Science, Computer Science, or ... Normal office environment. (Remote or Hybrid), 3 to 4 days per month are required in office if ...

Pepperidge Farm, Incorporated

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

The Data Science Analyst plays a critical role in supporting the Demand Planning function by ... Hybrid work model based in Camden, NJ (Monday & Friday remote; Tuesday-Thursday in-office) * 10-15 ...

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All JobsData Science Music JobsRemote Data Science Music JobsRemote Data Science Music Jobs in Philadelphia, PA

Remote Data Science Music information

See Philadelphia, PA salary details

$41.9K

$143.8K

$202.8K

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

As of Jul 29, 2026, the average yearly pay for remote data science music in Philadelphia, PA is $143,755.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,600.00 and $168,000.00 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.
What are the most commonly searched types of Data Science Music jobs in Philadelphia, PA? The most popular types of Data Science Music jobs in Philadelphia, PA are:
What are popular job titles related to Remote Data Science Music jobs in Philadelphia, PA? For Remote Data Science Music jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Remote Data Science Music jobs in Philadelphia, PA look for? The top searched job categories for Remote Data Science Music jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Remote Data Science Music jobs? Cities near Philadelphia, PA with the most Remote Data Science Music job openings:
Remote Data Science Music jobs near you
Infographic showing various Remote Data Science Music job openings in Philadelphia, PA as of July 2026, with employment types broken down into 1% As Needed, 78% Full Time, 13% Part Time, and 8% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution, with an average salary of $143,755 per year, or $69.1 per hour.

Senior Director of Data Science (Remote)

Forbes Advisor

Wilmington, DE • On-site, Remote

Full-time

Posted 22 days ago

Job description

At Forbes Advisor, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance so they can make informed decisions they feel confident in and get back to doing the things they care about most.
We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Forbes Advisor boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Forbes Advisor's global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel.
Our Data & Analytics organisation builds the products, platforms and intelligence that power every marketing, product and commercial decision across the business. We're looking for a Data Science leader who believes machine learning only creates value when it changes business decisions.
This is an opportunity to build and lead a commercially driven Data Science function that delivers measurable improvements in customer acquisition, marketing performance and long-term business growth.
You'll lead a growing team of Data Scientists while partnering closely with Engineering, Analytics, Product and Commercial teams to ensure predictive models become trusted, production-ready products that drive measurable commercial outcomes. As we continue investing in first-party data, AI, machine learning and advanced marketing measurement, we're looking for an experienced Data Science leader to help shape the next phase of our commercial Data Science capability.
Responsibilties:
  • Commercial Data Science: Lead the strategy and delivery of predictive models that improve customer acquisition, marketing performance and long-term commercial value. You'll shape capabilities including lifetime value modelling, propensity modelling, customer segmentation, forecasting and value-based bidding, ensuring every model is linked to measurable business outcomes.
  • Marketing Science & Decision Science: Partner with Marketing, Product and Commercial teams to apply Data Science to real business problems. You'll help define how predictive analytics, experimentation and AI improve campaign performance, customer understanding and strategic decision making across platforms including Google and Meta.
  • Production Data Science: Work closely with Engineering and ML Ops to ensure models become reliable, production-ready products rather than one-off analyses. You'll champion reproducible experimentation, scalable deployment, model monitoring, retraining strategies and continuous improvement throughout the model lifecycle.
  • Leadership & Stakeholder Management: Lead and develop a growing team of Data Scientists while building trusted relationships across the business. You'll translate complex modelling into clear commercial recommendations, influence senior stakeholders through evidence, and help establish Data Science as a trusted driver of business strategy and commercial growth.
  • Innovation & Industry Leadership: Represent Forbes in strategic conversations with technology partners including Google and Meta while staying connected to advances in AI, machine learning and marketing science. You'll evaluate emerging technologies, bring new ideas into the organisation and help ensure our Data Science capability remains commercially relevant and technically leading.

Qualifications:
  • Experience leading commercial Data Science, Marketing Science or Decision Science teams.
  • Strong expertise in predictive analytics, customer analytics, machine learning and statistical modelling.
  • Experience applying Data Science to marketing performance, customer acquisition, lifetime value or value-based bidding.
  • Experience productionising machine learning solutions within modern cloud environments and working closely with Engineering and ML Ops teams.
  • Strong understanding of SQL, Python and modern machine learning frameworks.
  • Experience working with Google Ads, Meta or other major advertising platforms.
  • Excellent stakeholder management and communication skills, with the ability to influence both technical and commercial audiences.
  • Experience building and developing high-performing Data Science teams.
  • Strong commercial judgement, balancing technical excellence with measurable business impact.
  • A pragmatic approach to AI, applying emerging technologies where they create genuine commercial value.

Nice to Have
  • Experience within affiliate marketing, digital publishing or lead-generation businesses.
  • Experience working in financial services, insurance or regulated industries.
  • Experience working directly with Google or Meta Data Science teams.
  • Experience with attribution modelling and marketing measurement.
  • Experience building optimisation algorithms for DSPs or advertising platforms.
  • Experience with causal inference, experimentation frameworks or incrementality testing.
  • Experience forecasting marketing or commercial performance.
  • Experience with Vertex AI or equivalent cloud-based machine learning platforms.

Forbes Advisor provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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