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Entry Level Remote Data Modeler Jobs in Ann Arbor, MI

Your work will shape how models learn, reason, and perform through high-quality, real-world input ... clinical data sources. * Provide expert insights on structure-activity and structure-property ...

Staff Site Reliability Engineer

Ann Arbor, MI · On-site +1

$55.75 - $74/hr

Sight Machine strengthens manufacturers by providing the industry's only standard data model and ... We do have a remote-friendly culture with people based all around the US and the rest of the world.

Systems Integration Developer

Ann Arbor, MI · On-site +1

$150K - $180K/yr

Ability to build robust data models and reporting pipelines. * Familiarity with Azure services ... Hybrid schedule, may be considered for remote eligible The annualized base salary range for this ...

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Entry Level Remote Data Modeler information

See Ann Arbor, MI salary details

$10

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$81

How much do entry level remote data modeler jobs pay per hour?

As of Aug 25, 2026, the average hourly pay for entry level remote data modeler in Ann Arbor, MI is $57.44, according to ZipRecruiter salary data. Most workers in this role earn between $51.49 and $66.78 per hour, depending on experience, location, and employer.

What does an entry level remote data modeler do?

An Entry Level Remote Data Modeler assists in designing, creating, and maintaining data models that organize and structure information for companies, typically while working from home. They work closely with data architects and analysts to translate business requirements into technical data structures, such as databases or data warehouses. Their tasks may include creating diagrams, documenting data flows, and ensuring data integrity. This role often requires proficiency in data modeling tools and a basic understanding of databases and data management concepts.

What are the key skills and qualifications needed to thrive as an entry level remote data modeler, and why are they important?

To thrive as an Entry Level Remote Data Modeler, you need foundational knowledge in database concepts, data modeling principles, and a relevant degree in computer science or information systems. Familiarity with tools like ER/Studio, Microsoft Visio, and SQL-based database systems is typically expected. Strong analytical thinking, attention to detail, and effective communication are standout soft skills for this role. These skills and qualities are important because they ensure accurate data structure design, collaboration with remote teams, and successful implementation of data solutions.

What are the typical challenges faced by entry level remote data modelers, and how can they overcome them?

Entry-level remote data modelers often face challenges such as limited access to immediate mentorship, difficulty understanding complex data structures, and ensuring clear communication with distributed teams. To overcome these obstacles, it’s important to proactively seek feedback through regular virtual meetings, utilize collaboration platforms for documentation and model sharing, and participate in online forums or communities for peer support. Building a habit of clear, detailed documentation and asking clarifying questions early can also help navigate the learning curve and contribute effectively to team projects.

What is the difference between Entry Level Remote Data Modeler vs Entry Level Remote Data Analyst?

AspectEntry Level Remote Data ModelerEntry Level Remote Data Analyst
Primary FocusDesigning and developing data models and database structuresAnalyzing data sets to identify trends and generate reports
Required SkillsData modeling, SQL, database design, understanding of data architectureData analysis, Excel, SQL, visualization tools
Work EnvironmentRemote, often collaborating with data engineers and developersRemote, working with business teams and stakeholders
Common CertificationsNone required but beneficial: Microsoft Certified Data Analyst, IBM Data ScienceNone required but beneficial: Microsoft Certified Data Analyst, Google Data Analytics

While both roles are entry-level and often remote, data modelers focus on structuring and designing data systems, whereas data analysts interpret data to support decision-making. Understanding these differences helps job seekers target the right roles based on their skills and career goals.

What are popular job titles related to Entry Level Remote Data Modeler jobs in Ann Arbor, MI?

For Entry Level Remote Data Modeler jobs in Ann Arbor, MI, the most frequently searched job titles are:

What cities near Ann Arbor, MI are hiring for Entry Level Remote Data Modeler jobs?

Cities near Ann Arbor, MI with the most Entry Level Remote Data Modeler job openings:

Infographic showing various Entry Level Remote Data Modeler job openings in Ann Arbor, MI as of August 2026, with employment types broken down into 1% As Needed, 88% Full Time, 9% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $119,477 per year, or $57.4 per hour.

Data Scientist - Machine Learning Practitioner

Ann Arbor, MI • On-site, Remote

BlueConduit
Internet and IT • 11 - 50 employees

$140K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 10 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