Risk Analytics Specialist
WSP View all jobs
- Toronto, ON
- $104,100-138,000 per year
- Permanent
- Full-time
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We are WSP.The OpportunityYour impact starts here. As a Quantitative Risk Analytics Specialist, you will apply advanced quantitative methods to help shape safe, resilient and sustainable outcomes across mining, resources, infrastructure and environmental projects. This role can be based anywhere in Canada.You will lead and deliver complex risk analytics assignments, developing probabilistic models, simulations and decision-support tools that help our clients understand uncertainty, interdependencies and potential impacts on their assets and operations. Partnering with multi-disciplinary teams across WSP, you will turn data and domain knowledge into insights that support risk management strategies, regulatory compliance and critical investment and operational decisions.Your ImpactIn this role, you will:
- Lead and deliver quantitative risk analytics for mining, resource, infrastructure and environmental projects, from scoping and data collection through to modeling, interpretation and recommendations.
- Develop and implement probabilistic models and simulations (including Monte Carlo-based approaches) to quantify uncertainty, evaluate risk exposure and support decision-making for complex engineering and operational systems.
- Apply and tailor risk modeling methodologies such as Fault Tree Analysis (FTA), Event Tree Analysis (ETA) and Quantitative Risk Assessment (QRA) to assess safety, environmental and operational hazards across projects.
- Design and run scenario and sensitivity analyses to test risk response options, mitigation strategies and investment choices under different assumptions and future conditions.
- Translate engineering and operational problems into quantitative models, clearly documenting assumptions, data sources, limitations and implications for decision-makers.
- Work closely with technical specialists and project managers across WSP to embed risk analytics into broader project frameworks, linking to design, environmental assessment, permitting, cost and schedule, and asset management.
- Prepare clear, concise reports, visualizations and presentations that communicate complex analytical findings to both technical and non-technical audiences, including clients and senior stakeholders.
- Facilitate and contribute to multi-disciplinary risk workshops, guiding subject matter experts through structured risk identification, evaluation and prioritization processes.
- Support the development and continuous improvement of internal tools, templates and best practices for quantitative risk analytics, and provide mentorship on methods and approaches where appropriate.
- 5-10 years of experience in risk analytics, ideally applied within mining, infrastructure, energy, resource or environmental risk domains.
- A Master's degree or PhD (or equivalent experience) in Statistics, Applied Mathematics, Data Science, Engineering or a related field, with a strong foundation in probability, statistics and uncertainty analysis.
- Demonstrated experience with Monte Carlo simulation and probabilistic risk modeling, including scenario and sensitivity analysis for complex systems.
- Experience modeling interdependencies between risks and system components.
- Familiarity with risk modeling methodologies such as FTA, ETA and QRA, and the ability to adapt them to different project and regulatory contexts.
- Proficiency in Python or R for data analysis and modeling, including building reproducible analytical workflows and leveraging relevant statistical and simulation libraries.
- Experience working with structured and unstructured data to support quantitative modeling and analytics
- Proven ability to translate engineering or operational questions into quantitative models, and to clearly explain model logic and results to diverse audiences.
- Experience working with and guiding diverse teams of subject matter experts and facilitating workshops or risk sessions in multi-stakeholder environments.
- Strong skills in communicating analytical insights, ideally supported by data visualization tools (e.g., Power BI, Tableau or Python visualization libraries).
- An asset (nice to have):
- Experience with probabilistic modeling of risk interdependencies.
- Knowledge of machine learning, predictive analytics and optimization methods in a risk context.
- Exposure to financial risk modeling or cost-risk analysis, linking risk outcomes to business cases and investment decisions.
- Knowledge of reliability engineering or probabilistic failure analysis.
- Experience working with cloud or modern data platforms (e.g., Azure, AWS or GCP).
- Proudly Canadian - we are a Top 100 Employer in Canada for 2026.
- A global community of brilliant minds - your next idea, mentor or opportunity is always within reach.
- Limitless opportunities start here. Whether it's across the country or around the globe, we help you tailor your role to match your ambition - because your growth drives ours.
- Flexible work, real balance - we recognize the importance of balance in our lives and encourage you to prioritize the balance in yours.
- AB, BC, NT, NU, SK & YT: $104,100 - $138,000
- MB & ON: $95,000 - $130,800
- NB, NL, NS, PEI & QC: $94,100 - $124,900
The final salary awarded for this role may vary from the above range based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, seniority, geographic location, performance, and business or organizational needs. The wage range provided in this job posting may be subject to change for business purposes.Join Us in Making an ImpactIf you're ready to bring your risk analytics expertise to projects that matter, we want to hear from you. Apply now and let's build something great together.About Us:WSP is one of the world's leading professional services firms. Our purpose is to future proof our cities and environments.We have over 65,000 team members across the globe. In Canada, our 12,000+ people are involved in everything from environmental remediation to urban planning, from engineering iconic buildings to designing sustainable transportation networks, from finding new ways to extract essential resources to developing renewable power sources for the future.At WSP:
- We value our people and our reputation
- We are locally dedicated with international scale
- We are future focused and challenge the status quo
- We foster collaboration in everything we do
- We have an empowering culture and hold ourselves accountable