Data Scientist developing network - based financial - crime detection for TD Bank. Building models, visualizations, and decision - support tools to prioritize high - risk customer connections.
About the role
- Senior Data Scientist at Darkhorse Emergency designing data models and predictive analytics for emergency services. Leading comprehensive risk assessments and mentoring junior team members in statistical methods.
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.
Requirements
- 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.
Benefits
- Health insurance
- Professional development opportunities
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