About

• What You’ll Be Doing
• Work at Darkhorse Emergency is diverse and ever-changing. We help fire, EMS, and police services save lives through data-driven decisions — optimizing where stations are located, how resources are deployed, and how risk is assessed across communities. Built on pioneering academic research, our platform combines comprehensive reporting with advanced statistical modelling, geospatial analysis, and optimization algorithms to revolutionize how emergency services plan and operate in their communities. Every client is different. The interpretation of their data and unique needs requires strong analytical skills.
• As a senior data scientist, you will take ownership of creating, implementing, maintaining, and improving all the mathematical and statistical modelling in our platform. Your key accountability will be that our methods are validated and useful for our customers' needs. You own methodological decisions and are accountable for the validity of models delivered to clients. Your work will be conducted without routine review or supervision. You’ll spend time reviewing the work of junior team members and provide leadership as needed.
• You’ll be pulled in competing directions: focused on the long term, but frequently pulled into the immediate needs of clients. You will navigate the difficult balance between duct-taping what’s there to solve the problems of today, and building it right to solve the problems of tomorrow.
• Job Responsibilities
• Independently design and implement comprehensive risk assessment models that combine geographic, demographic, and emergency response data.
• Develop and enhance predictive models for detailed, spatially accurate emergency service demand forecasting, incorporating demographic trends and urban development patterns.
• Create and validate response time models using routing algorithms tuned to real-world emergency vehicle data.
• Optimize emergency response coverage through facility location and resource deployment models using linear programming and metaheuristic optimization.
• Build and maintain data pipelines in Postgres, PostGIS and AWS that integrate diverse data sources, including demographic, geographic, and historical response data.
• Evaluate and adopt AI tools and techniques that improve the team's analytical and development workflows, and help junior team members integrate them effectively.
• Write reliable, unit-tested SQL and Python code to bring models into production.
• Work with front end developers to incorporate our models into the apps our customers use.
• Collaborate directly with domain experts on our customer team, as well as emergency services stakeholders, to understand their needs and validate solutions.
• Create documentation, training materials and provide support for team members relying on your expertise.
• Support, mentor and guide junior data scientists in basic processes.
• What We Look For
• Advanced degree (MSc or PhD) in Statistics, Operations Research, Applied Mathematics, or related quantitative field
• Five or more years of experience with statistical modelling, machine learning, and optimization algorithms.
• Expertise in geospatial analysis and GIS technologies.
• Proficient in Python programming, with experience in scientific computing libraries (NumPy, SciPy, scikit-learn).
• Experience with SQL and spatial databases.
• Demonstrated ability to translate complex mathematical concepts into practical solutions.
• Creatively problem-solving complex and multi-faceted issues in order to find the right trade-offs and compromises using experience manuals and best practices.
• You value autonomy and take pride in doing your best work even when nobody’s watching.
• You're excited about applying advanced analytical techniques to solve real-world problems.
• You can balance theoretical rigor with practical implementation.
• You have a passion for public safety and emergency services.
• You share and live our values every day.
• Experience with QGIS or similar GIS platforms would be considered an asset.
• Familiarity with optimization solvers (e.g., Gurobi) and metaheuristic algorithms would be considered an asset.
• Knowledge of emergency services operations or public safety would be considered an asset.
• Experience with routing algorithms and transportation network analysis would be considered an asset.
• Background in risk assessment or predictive modelling for critical services would be considered an asset.
• Track record of implementing mathematical models in production environments would be considered an asset.
• Key Skills
• Leverage AI tools and LLMs to accelerate data transformation, analysis, and code development, and champion their adoption across the team.
• Communicate analytical results through clear, effective visualizations
• Craftsmanship
• Project management
• Initiative and innovation
• Act as a role model for company career development, morale building and evangelism
• Navigate ambiguity of competing priorities and resource constraints
• Quality oriented
• Accuracy and detail oriented