Top Tech Jobs & Startup Jobs in Montreal

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.

Lead integration of AI-driven tools into tax provision, planning, and multi-jurisdictional compliance. Design ML/analytics solutions for sales and payroll tax, enhance regulatory filings, support audits, and collaborate with finance, legal, and technology teams. Monitor tax regulation changes, document AI tax models for transparency and governance, and continuously refine models for scalability, reliability, and compliance.

Serve as the internal customer advocate and technical pre-sales lead for finance-heavy billing and revenue recognition solutions. Translate complex billing and revenue requirements into configured demos, sandbox environments, and solution documents. Partner with Sales, Product, and Engineering to support discovery, RFPs, implementations, and handoffs for enterprise customers.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

Review and assess equity research, models, and market analyses to improve AI training data. Provide valuation, earnings forecasting, and investment memo feedback using long/short equity frameworks. Contribute to analytical materials, market sizing, and research summaries to enhance financial reasoning in foundational models.

Analyze and classify technical content for security vulnerabilities, apply pattern recognition to improve AI model threat detection, design and evaluate security problems, and collaborate asynchronously with domain experts to produce high-quality outputs.

Contribute transactional and corporate law expertise to train and evaluate AI models: design realistic deal scenarios, draft attorney-quality gold-standard responses, grade AI outputs with rubrics, provide written feedback to improve model reasoning, and participate in onboarding and calibration sessions.

Act as the internal voice of the customer, partnering with Sales, Product, and Engineering to design and configure billing, revenue recognition, and invoicing solutions. Lead discovery with finance leaders, build demo/sandbox environments, respond to RFPs, document handoffs, and create onboarding materials while advocating customer needs to Product and Engineering.

Design institutional-quality, transaction-oriented financial modeling tasks and gold-standard reference models to train AI. Build and review integrated 3-statement models, DCFs, LBOs, M&A and growth equity frameworks, perform diligence and sensitivity analyses, document assumptions, and collaborate asynchronously with AI researchers.

Design, implement, and monitor AI/ML models to improve underwriting risk assessment, pricing, and portfolio management. Translate underwriting rules into data models, integrate models into workflows, analyze datasets for risk patterns, build decision-support tools, ensure compliance and fairness, and collaborate with underwriting, actuarial, product, and engineering teams.