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Remote Data Analysis Jobs in Novi, MI (NOW HIRING)

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

This remote role may require occasional travel to client sites located in Ohio, Pennsylvania ... Experience using Excel for data analysis, including vlookups, xlookups and pivot tables * Ability ...

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

Showing results 21-40

Remote Data Analysis information

What are the key skills and qualifications needed to thrive as a remote data analyst?

To thrive as a Remote Data Analyst, you need strong analytical skills, statistical knowledge, and a background in fields like mathematics, statistics, or computer science. Proficiency with data analysis tools such as SQL, Python, R, and visualization platforms like Tableau or Power BI is typically required. Excellent communication, self-motivation, and time management help remote analysts present insights clearly and stay productive without direct supervision. These skills and qualities ensure accurate data-driven decisions and effective remote collaboration with stakeholders.

What is the difference between Remote Data Analysis vs Remote Data Entry?

AspectRemote Data AnalysisRemote Data Entry
Required SkillsData interpretation, statistical tools, analytical skillsTyping speed, accuracy, basic computer skills
Tools UsedExcel, SQL, data visualization softwareSpreadsheets, data entry platforms
Work EnvironmentAnalytical tasks, report creation, data insightsData input, database updating, record management
Common CertificationsData analysis certifications, Excel proficiencyNone typically required

Remote Data Analysis involves interpreting data, creating reports, and providing insights using analytical tools, while Remote Data Entry focuses on inputting and managing data accurately. Both roles are performed remotely and require computer skills, but Data Analysis demands analytical expertise and familiarity with data tools, whereas Data Entry emphasizes speed and accuracy in data input tasks.

What is remote data analysis?

Remote data analysis refers to the process of examining, interpreting, and drawing insights from data using digital tools, while working from a location outside of a traditional office setting. Professionals in this field utilize statistical software, databases, and visualization tools to analyze large datasets and help organizations make informed decisions. Remote data analysts often collaborate with team members and stakeholders virtually, ensuring that data-driven strategies are implemented effectively. This role requires strong analytical skills, attention to detail, and the ability to communicate findings clearly.

How do remote data analysts typically collaborate with team members and stakeholders?

Remote data analysts often use a combination of communication and project management tools—such as Slack, Microsoft Teams, and Zoom—to stay connected with colleagues and stakeholders. Regular virtual meetings, shared dashboards, and collaborative platforms enable them to discuss findings, gather requirements, and provide updates on ongoing projects. Clear documentation and proactive communication are essential to ensure alignment, especially when working across different time zones or departments. Building strong relationships with team members virtually can help streamline workflows and facilitate effective decision-making.

What are the most commonly searched types of Data Analysis jobs in Novi, MI?

The most popular types of Data Analysis jobs in Novi, MI are:

What are popular job titles related to Remote Data Analysis jobs in Novi, MI?

For Remote Data Analysis jobs in Novi, MI, the most frequently searched job titles are:

What job categories do people searching Remote Data Analysis jobs in Novi, MI look for?

The top searched job categories for Remote Data Analysis jobs in Novi, MI are:

What cities near Novi, MI are hiring for Remote Data Analysis jobs?

Cities near Novi, MI with the most Remote Data Analysis job openings:

Infographic showing various Remote Data Analysis job openings in Novi, MI as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 15% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution.

Data Scientist -- Machine Learning Practitioner

BlueConduit

Ann Arbor, MI • On-site, Remote

$150K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 29 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