Data Wildfire Data Scientist Remote · Remote — U.S. View role

Cindera Inc.; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Remote work

Job summary

Cindera Inc. is seeking a senior data scientist to translate wildfire hazard science into parcel-level readiness scores that are explainable and actionable for homeowners, insurers, and vendors.

You will work with data, product, and domain experts to define risk measurement, action-driven scoring, and transparent confidence assessments. The role involves end-to-end ownership of modeling problems, from data design and feature engineering through calibration and iteration as new evidence emerges.

Qualifications

• 5+ years of applied data science or ML in production.
• Experience with geospatial, property, or insurance data.
• Ability to explain modeling choices to non-technical partners.
• Experience shipping data products.
• Proficiency with data pipelines and calibration.

Responsibilities

• Build parcel-level readiness scores using hazard data, mitigation standards, and actions.
• Design feature sets and modeling approaches for exposure, vulnerability, and impact.
• Turn research outputs into production data pipelines and systems.
• Evaluate model performance, calibration, drift, and uncertainty.
• Encode wildfire science and mitigation logic transparently for customers.

Skills

Applied DS

Statistical modeling

Machine learning

Production ML

Geospatial data

Feature engineering

Model evaluation

Uncertainty

Explainability

Data pipelines

Education

MS in Data Science or related field

BS in Computer Science, Statistics, or related field

Tools

Python

SQL

Spark

GeoPandas

Git

Airflow

Job description

Turn wildfire hazard science, mitigation standards, and verified homeowner actions into parcel-level readiness scores people and carriers can trust. This is a senior data role focused on making complex risk signals usable in real decisions.

Remote · Remote — U.S. Posted August 6, 2026

Competitive compensation with meaningful equity; details discussed during the process.

The opportunity

Cindera helps homeowners, insurers, and vendors understand wildfire risk and what can be done about it. This role sits at the center of that work: translating hazard science and mitigation standards into parcel-level readiness scores that are explainable, testable, and useful in practice.

You’ll work across data, product, and domain experts to define how risk should be measured, how verified actions should change a score, and how we show confidence and limitations. The work is technical, but it also has to hold up in the real world when a homeowner, underwriter, or mitigation provider looks at it and asks, “Can we trust this?”

We’re looking for someone who is comfortable owning ambiguous modeling problems end to end, from data design and feature engineering through evaluation, calibration, and ongoing iteration as new evidence comes in.

What you'd do

• Build and refine parcel-level readiness scores using hazard data, mitigation standards, and verified homeowner actions.
• Design feature sets and modeling approaches that capture wildfire exposure, vulnerability, and mitigation impact.
• Work with product and engineering to turn research outputs into reliable production systems and data pipelines.
• Evaluate model performance, calibration, drift, and uncertainty so scores remain useful and defensible over time.
• Partner with domain experts to encode wildfire science and mitigation logic in a way that is transparent to customers.

What we're looking for

• Strong experience with applied data science, statistical modeling, or machine learning in a production environment.
• Comfort working with messy geospatial, property, or insurance-related data and turning it into structured signals.
• Ability to explain modeling choices, tradeoffs, and limitations to non-technical partners.
• Track record of owning ambiguous problems and shipping data products that people actually use.
• Practical judgment about when a simpler approach is better than a more complex one.

Nice to have

• Experience with wildfire, climate risk, property risk, or insurance analytics.
• Hands-on work with geospatial data, remote sensing, or parcel-level property datasets.
• Familiarity with model calibration, interpretability, and risk scoring for decision support.
• Experience designing systems that incorporate verified user actions or inspection data.

Why Cindera

Cindera is building tools that make wildfire readiness more measurable and more actionable. The work is technical, but it is grounded in a real problem with real consequences for homeowners and the companies that serve them.

You’ll join a team that values clear thinking, domain rigor, and shipping useful systems over polished slides. If you want your modeling work to affect how risk is understood and reduced in the real world, this is a strong place to do it.