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Data Scientist Machine Learning Practitioner
- United States
- United States
À propos
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
Compétences linguistiques
- English
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