3

Entry Level Data Scientist Remote Jobs in Detroit, MI

Nurse Practitioner: Remote Urgent Care

Detroit, MI ยท Remote

$109K - $151K/yr

Belle uses cutting edge data science to identify those most in need on behalf of health plans and ... As these issues arise, a team of remote nurses coordinate care with other healthcare providers ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

... clinical data sources. * Provide expert insights on structure-activity and structure-property ... Assess and review AI-generated outputs for scientific rigor, accuracy, and practical relevance ...

next page

Showing results 1-20

Entry Level Data Scientist Remote information

See Detroit, MI salary details

$45.5K

$163.4K

$241.1K

How much do entry level data scientist remote jobs pay per year?

As of Aug 28, 2026, the average yearly pay for entry level data scientist remote in Detroit, MI is $163,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,200.00 and $168,300.00 per year, depending on experience, location, and employer.

What is an entry level data scientist remote?

An Entry Level Data Scientist (Remote) is a professional who analyzes and interprets complex digital data to help companies make informed decisions, typically working from a location outside of the company's physical office. They use statistical techniques, machine learning, and data visualization tools to uncover insights from large datasets. Entry level positions are designed for individuals with limited professional experience, often recent graduates or those transitioning into the field. Remote roles offer flexibility, enabling employees to work from home or any other location with internet access.

What are the key skills and qualifications needed to thrive as an entry level data scientist remote?

To thrive as an Entry Level Data Scientist (Remote), you need a solid foundation in statistics, programming (especially Python or R), and data analysis, typically supported by a degree in computer science, mathematics, or a related field. Familiarity with tools like SQL, Jupyter Notebooks, and machine learning libraries (such as scikit-learn or TensorFlow), as well as experience with data visualization platforms, is often expected. Strong problem-solving skills, self-motivation, and clear communication are crucial for collaborating across teams and working independently in a remote environment. These skills and qualities ensure you can effectively extract insights from data and contribute meaningfully to business decisions, even without direct in-person supervision.

What are some common challenges entry level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulties in understanding team expectations, and staying motivated without in-person supervision. To overcome these, it's helpful to proactively communicate with teammates and supervisors, seek regular feedback, and participate in virtual team meetings or collaborative coding sessions. Leveraging online communities and internal chat channels can also help build connections and access guidance when needed, ensuring continued learning and integration into the team.

Can I get an entry level data scientist remote job with no experience?

Entry level remote data scientist positions typically require some foundational knowledge in programming, statistics, and data analysis tools like Python or R. While prior experience is often preferred, candidates with relevant coursework, certifications, or strong analytical skills can sometimes qualify for entry-level roles without professional experience.

What job categories do people searching Entry Level Data Scientist Remote jobs in Detroit, MI look for?

The top searched job categories for Entry Level Data Scientist Remote jobs in Detroit, MI are:

What cities near Detroit, MI are hiring for Entry Level Data Scientist Remote jobs?

Cities near Detroit, MI with the most Entry Level Data Scientist Remote job openings:

Infographic showing various Entry Level Data Scientist Remote job openings in Detroit, MI as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 13% Part Time, and 2% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $163,362 per year, or $78.5 per hour.

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 12 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