2

Remote Data Science Music Jobs in Michigan (NOW HIRING)

Bachelor's degree in Data Science, Engineering, Mathematics, Computer Science, Operations Research ... Benefit Summary This role is remote but if you live within 50 miles within Dearborn, MI, you will ...

Director of Data Intelligence | Remote | Michigan or Minnesota Preferred Role Snapshot: * Set the ... Build and lead a high-performing team of data scientists, analysts, and engineers. * Promote a ...

Senior Staff Data Engineer

Portage, MI ยท On-site +1

$153K - $255K/yr

Remote Join a team focused on building scalable, enterprise-grade data platforms that support ... Bachelor's degree in Computer Science, Data Analytics, Mathematics, Statistics, Data Science, or a ...

next page

Showing results 1-20

Remote Data Science Music information

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 key skills and qualifications needed to thrive as a remote data science music professional?

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.

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 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 are the most commonly searched types of Data Science Music jobs in Michigan?

The most popular types of Data Science Music jobs in Michigan are:

What cities in Michigan are hiring for Remote Data Science Music jobs?

Cities in Michigan with the most Remote Data Science Music job openings:

Infographic showing various Remote Data Science Music job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 4% Contract, and 1% Nights. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution.

Data Scientist - Machine Learning Practitioner

BlueConduit

Ann Arbor, MI โ€ข On-site, Remote

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 23 days ago


Job description

Company overview

BlueConduit is an infrastructure analytics SaaS company and social enterprise helping communities make better, faster, and more equitable decisions about critical water infrastructure. Our founding team pioneered predictive modeling for lead service line replacement in Flint, Michigan, and BlueConduit now works with hundreds of cities and utilities across North America.

Our platform helps utilities, municipalities, government agencies, and consultants combine fragmented infrastructure records, field observations, geospatial data, and predictive models to identify risk, prioritize work, meet compliance requirements, and communicate clearly with the public. We are a remote-first team committed to using data science for social good and building tools that are trusted by the people making high-stakes infrastructure decisions.

The role

BlueConduit is hiring a Data Scientist to improve and expand the machine learning models at the core of our infrastructure analytics platform. In this role, you will work on models that help cities prioritize infrastructure investments, reduce risk, and improve drinking water outcomes. You will strengthen our existing modeling workflows, help launch new model products and asset classes, and communicate results clearly to both technical and nontechnical audiences.

This is a strong fit for someone who combines rigorous applied ML judgment with product-minded execution: you enjoy messy real-world data, care about model validation and uncertainty, can build repeatable workflows rather than one-off analyses, and like explaining technical work to people who need to act on it.

In this role you will be expected to be using the latest available AI tools to code productively. You will need to understand what you're building and coding, and understand agentic AI workflows that involve best practices, including unit tests, built-in code reviews, and extensive documentation in your commits for fellow data scientists and software engineers.

This role reports to the VP of Data Science.

What you'll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduit's infrastructure analytics products
  • Help design, build, and launch new model products and model classes that broaden the assets and risks BlueConduit can predict
  • Improve data science workflows, model evaluation, reproducibility, and handoffs into software/product systems
  • Work with heterogeneous municipal, infrastructure, geospatial, and field-observation datasets to generate actionable risk predictions
  • Design validation approaches and communicate model uncertainty, limitations, and tradeoffs clearly to internal teams and customers
  • Use modern AI coding tools such as Claude Code, Codex, or similar systems to accelerate development while applying strong independent programming judgment
  • Use multiple AI agents to contribute to extremely robust workflows and code pipelines with built-in testing and reviews
  • Support customer-facing analysis and present findings in ways that are clear, accurate, and useful for nontechnical decision-makers
  • Contribute to R&D that scales the impact, reliability, and reach of BlueConduit's predictive methods

BlueConduit is a small, remote, and growing team, so this is an opportunity to shape both the role and the next generation of our data science products.

What we're looking for
  • Strong Python-based data science experience, including pandas, NumPy, scikit-learn, and production-quality analysis workflows
  • An undergraduate degree in a quantitative field (e.g., CS, math, stats, physics)
  • Experience building, validating, and improving machine learning or statistical models on messy real-world data
  • Experience building repeatable data science workflows in a product at a SaaS company or similarly operational environment
  • Ability to communicate modeling results, uncertainty, and tradeoffs clearly to technical and nontechnical stakeholders
  • Fluency using modern AI coding tools - including coordinating work of AI agents - to accelerate development, grounded in strong independent programming ability and judgment
  • Strong data visualization, verbal communication, and written communication skills
  • Comfort with Git-based development workflows
  • Attention to detail, curiosity, and commitment to building models that are understandable, usable, and trusted by the people making infrastructure decisions
  • Passion for socially impactful data science, environmental justice, and public-interest technology
We're especially interested in candidates with one or more of the following
  • A rigorous graduate degree in a quantitative field, or equivalent applied experience
  • Experience modeling asset classes beyond BlueConduit's current water distribution portfolio, such as fire risk, wastewater, hydraulic systems, climate risk, insurance risk, or other infrastructure domains
  • Experience with geospatial data, GIS systems, GeoPandas, or spatial modeling
  • Experience creating a new model product or extending an existing model product to a new domain or asset class
  • Experience with both global/cross-location models and local/site-specific models
  • Experience with methodologies beyond classical ML, such as neural networks, transformers, transfer learning, or other modern ML approaches
  • Experience with cloud-based model workflows, model tracking, versioning, Databricks, PySpark, or distributed computing
  • Familiarity with infrastructure, water quality, government data, or regulated public-sector decision environments
  • Experience working in Agile product development environments
  • Aptitude and interest in building with rapid iteration cycles involving prototyping, receiving feedback, and rebuilding
Location

Remote

Compensation
  • Expected salary range: $140,000-$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching

Every qualified applicant will receive consideration for employment without regard to race, age, color, religion, sex, sexual orientation, or national origin.

Employment Type: FULL_TIME