Staff Applied Scientist (Distribution Center Solutions)
Job Description
Team: Analyst
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.
- 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.
- 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.
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Date Posted
07/06/2026
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