**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff Applied Scientist (Distribution Center Solutions) based in Canada.** This role sits at the intersection of machine learning, operations research, and large-scale optimization, focused on solving one of the most complex problems in modern supply chains: perishable inventory management. You will develop and refine advanced models that power real-time decision-making systems responsible for ordering and distributing fresh goods at massive scale. The position requires deep analytical expertise to tackle uncertainty in demand, supply variability, product decay, and multi-echelon distribution constraints. Your work will directly influence how millions of products are replenished daily, reducing food waste and improving freshness across retail networks. You will collaborate in a highly technical environment where research, simulation, and production-grade engineering are tightly integrated. The role combines scientific innovation with real-world impact, turning advanced modeling into systems that operate in production from day one. This is a high-ownership position where your contributions shape both the technical direction and global impact of AI-driven supply chain optimization. ### Accountabilities: - Lead research and development efforts for AI/ML-driven replenishment and optimization systems within large-scale distribution center operations. - Design and implement advanced models for demand forecasting, inventory decay, price elasticity, promotions, and stochastic supply chain behavior. - Develop and optimize multi-echelon inventory control systems using techniques from machine learning, operations research, and stochastic optimization. - Translate complex mathematical and research concepts into production-grade systems using scalable and well-tested code. - Own the end-to-end lifecycle of modeling initiatives, from research and experimentation to deployment and performance monitoring. - Evaluate model performance rigorously through simulation, A/B testing, and real-world validation frameworks. - Collaborate with engineering and product teams to define technical direction and align research priorities with business impact. - Mentor other scientists and engineers, raising the bar for experimental rigor, modeling quality, and system design. - Contribute to architectural decisions and ensure scalability, reliability, and maintainability of production systems. - Continuously explore and integrate new methodologies in AI, optimization, and decision science to improve system performance. ## Requirements - Advanced degree (MS or PhD) in Operations Research, Industrial Engineering, Computer Science, Electrical Engineering, Mathematics, or a related quantitative field. - 4+ years of industry experience for PhD holders or 8+ years for MS holders working on applied machine learning, optimization, or decision systems. - Strong background in stochastic optimization, forecasting, simulation, or large-scale decision-making under uncertainty. - Proven experience building and deploying production systems that integrate ML models with real-world operational constraints. - Strong programming skills in Python and related data/ML stacks such as NumPy, PyTorch, and pandas. - Experience modeling complex systems such as supply chains, inventory optimization, or dynamic pricing is highly desirable. - Ability to clearly communicate complex technical and mathematical concepts to both technical and non-technical stakeholders. - Strong experimental mindset with experience in designing, validating, and iterating on ML-driven systems. - Excellent collaboration skills and experience working cross-functionally with engineering and product teams. - Nice to have: familiarity with distributed systems, ML platforms, or applied research in operations research or reinforcement learning. ## Benefits - Fully remote work within Canada - Competitive salary range aligned with senior applied science roles - Comprehensive health, dental, and vision coverage for employees and families - Mental health and wellness support programs - Generous paid time off and flexible working arrangements - Home office and coworking stipends for flexible work setup - Annual professional development budget for continuous learning - Equity package (where applicable) and long-term incentive opportunities - High-impact role with measurable contribution to reducing global food waste - Collaborative, research-driven environment with strong focus on innovation and experimentation. **How Jobgether works:** We use an **AI-powered matching process** to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! [Why Apply Through Jobgether?](https://jobgether.com/how-jobgether-works) **Data Privacy Notice:** By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. #LI-CL1