Data Scientist — Machine Learning Practitioner

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.

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.

• →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.

• 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

• 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

Remote