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Full Time Remote Data Modeler Jobs in Detroit, MI

Principal Data Engineer

Ann Arbor, MI ยท On-site +1

$170K - $210K/yr

Architect and contribute directly to core platform components, including ingestion pipelines, transformation frameworks, data models, and orchestration * Define and evolve the multi-quarter technical ...

Principal Data Engineer

Plymouth, MI ยท Remote

$109K - $130K/yr

Remote Employment: Full Time Location: US Seniority: Senior Level Technologies: Tableau, Tableau ... Data and Analytics

Engineering & Science Job Schedule: Full time Remote: No The Opportunity: JR Automation, a Hitachi ... Develop simulation standards, processes, models, and scripts/control. * Provide high quality ...

Engineering & Science Job Schedule: Full time Remote: No The Opportunity: JR Automation, a Hitachi ... Develop simulation standards, processes, models, and scripts/control. * Provide high quality ...

Showing results 21-40

Full Time Remote Data Modeler information

See Detroit, MI salary details

$10

$58

$82

How much do full time remote data modeler jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for full time remote data modeler in Detroit, MI is $58.12, according to ZipRecruiter salary data. Most workers in this role earn between $52.12 and $67.60 per hour, depending on experience, location, and employer.

How do full time remote data modelers typically collaborate with distributed teams to ensure data consistency and project alignment?

Full Time Remote Data Modelers usually work closely with other data professionals, such as data engineers, analysts, and business stakeholders, using collaborative tools like shared documentation, version control systems, and virtual meetings. Clear communication and regular sync-ups are essential to ensure everyone understands the data models and that standards are consistently applied across projects. These professionals often participate in daily stand-ups, design reviews, and cross-functional team discussions to address challenges, clarify requirements, and maintain alignment with business goals. Remote work requires proactive communication and a disciplined approach to documentation to avoid misinterpretations and ensure data integrity.

What is the difference between Full Time Remote Data Modeler vs Full Time Remote Data Analyst?

AspectFull Time Remote Data ModelerFull Time Remote Data Analyst
Primary RoleDesigns and develops data models and database structuresAnalyzes data to generate reports and insights
Required SkillsData modeling, database design, SQL, data warehousingData analysis, visualization, SQL, statistical tools
Work EnvironmentRemote, often collaborating with data engineers and architectsRemote, working with business teams and stakeholders
Common CertificationsCDMP, CBIP, Microsoft Certified Data AnalystMicrosoft Certified Data Analyst, SAS, Tableau certifications

While both roles work remotely and require SQL and data skills, a Full Time Remote Data Modeler focuses on designing data structures, whereas a Full Time Remote Data Analyst interprets data to support business decisions. They complement each other but serve different functions within data teams.

What is a full time remote data modeler?

Full Time Remote Data Modelers are professionals who design, create, and maintain data models for organizations while working from a remote location. Their main responsibility is to structure and organize data so it can be efficiently stored, accessed, and analyzed, often collaborating with data engineers, analysts, and other IT staff. Working full time means they typically work a standard 40-hour week, and since the role is remote, all communication and collaboration are done virtually. These professionals are essential for organizations that rely heavily on data-driven decision making and need robust data infrastructure. They often use tools like ERwin, SQL, or PowerDesigner and are skilled in database management and programming.

What are the key skills and qualifications needed to thrive as a full time remote data modeler?

To thrive as a Full Time Remote Data Modeler, you need expertise in database design, data modeling concepts (such as ER diagrams and normalization), and a degree in computer science or a related field. Familiarity with data modeling tools (like ER/Studio, Erwin, or SQL-based platforms) and experience with cloud databases are commonly required. Strong analytical thinking, attention to detail, and effective remote communication skills help you excel in collaborating with distributed teams. These skills are crucial for ensuring accurate data structures, efficient data flow, and seamless integration in complex, remote-driven projects.
What are popular job titles related to Full Time Remote Data Modeler jobs in Detroit, MI? For Full Time Remote Data Modeler jobs in Detroit, MI, the most frequently searched job titles are:
What job categories do people searching Full Time Remote Data Modeler jobs in Detroit, MI look for? The top searched job categories for Full Time Remote Data Modeler jobs in Detroit, MI are:
What cities near Detroit, MI are hiring for Full Time Remote Data Modeler jobs? Cities near Detroit, MI with the most Full Time Remote Data Modeler job openings:
Infographic showing various Full Time Remote Data Modeler job openings in Detroit, MI as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $120,897 per year, or $58.1 per hour.

Data Scientist -- Machine Learning Practitioner

BlueConduit

Ann Arbor, MI โ€ข On-site, Remote

Full-time

Medical, Dental, Vision, Retirement

Re-posted 25 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 youโ€™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 youโ€™ll do
  • Build, validate, and improve machine learning and statistical models used in BlueConduitโ€™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 BlueConduitโ€™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 weโ€™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 โ€“ including coordinating work of AI agents โ€“ 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
Weโ€™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 BlueConduitโ€™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: $140,000โ€“$150,000, commensurate with experience
  • Equity options
  • Health, vision and dental benefits
  • Simple IRA benefit with company contribution matching