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Remote Climate Analytics Jobs in Michigan (NOW HIRING)

Dam Safety Engineer

Marquette, MI · On-site +1

$85K - $120K/yr

A fully remote option may be available for the right candidate. Candidate will be part of a ... Example analyses might include layout and sizing of spillways and stilling basins, performing ...

Remote Climate Analytics information

How does a remote climate analytics professional typically collaborate with cross-functional teams?

Remote Climate Analytics professionals often work closely with data scientists, environmental researchers, and policy experts to interpret climate data and generate actionable insights. Collaboration is typically facilitated through virtual meetings, shared data platforms, and project management tools, ensuring seamless communication across different time zones. Regular updates and presentations are common, allowing the team to align on research goals and adapt to emerging climate trends or data challenges. This collaborative structure helps ensure that analytics outputs are both scientifically robust and aligned with stakeholder needs.

What are the key skills and qualifications needed to thrive as a remote climate analytics professional, and why are they important?

To thrive as a Remote Climate Analytics professional, you need a strong background in environmental science, data analysis, and statistics, often supported by a relevant degree or specialized training. Familiarity with climate modeling software, geographic information systems (GIS), programming languages like Python or R, and data visualization tools is typically required. Excellent problem-solving, communication, and critical thinking skills help you interpret complex data and collaborate with stakeholders. These competencies are essential for producing actionable insights that inform climate policy and drive effective environmental solutions.

What is a remote climate analytics?

A remote climate analytics job involves analyzing climate data and trends to inform policy, research, or business decisions, all while working from a location outside of a traditional office. Professionals in this field use tools like statistical software, climate models, and geographic information systems to interpret environmental data. They may work for government agencies, private companies, or research institutions, collaborating virtually with other team members. This role is ideal for individuals with strong analytical skills and a background in environmental science, data science, or related fields.

What is the difference between Remote Climate Analytics vs Remote Environmental Data Analyst?

AspectRemote Climate AnalyticsRemote Environmental Data Analyst
Required CredentialsBachelor's in Environmental Science, Climate Science, or related fields; often requires data analysis certificationsBachelor's in Environmental Science, Data Analysis, or related fields; may include certifications in GIS or data tools
Work EnvironmentRemote, often collaborative with climate research teams or NGOsRemote, typically working with environmental agencies or consulting firms
Employer & Industry UsageResearch institutions, climate organizations, NGOsGovernment agencies, environmental consultancies, research firms
Common Search & ComparisonYesYes

Remote Climate Analytics focuses on analyzing climate data and modeling climate change impacts, often working with specialized climate datasets. Remote Environmental Data Analysts handle broader environmental data, including pollution, conservation, and resource management. While both roles require data analysis skills and environmental knowledge, Remote Climate Analytics emphasizes climate-specific expertise, making it distinct in scope and focus.

What job categories do people searching Remote Climate Analytics jobs in Michigan look for?

The top searched job categories for Remote Climate Analytics jobs in Michigan are:

Data Scientist -- Machine Learning Practitioner

BlueConduit

Ann Arbor, MI • On-site, Remote

$150K/yr

Full-time

Medical, Dental, Vision, Retirement

This job post has expired today. Applications are no longer accepted.


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