Senior Applied Scientist, Parts Intelligence & Inventory Optimization
MaintainX - Canada (Remote)
Posted Jun 2, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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Market context
- Median wage (BLS OEWS)
- $111,944 national median
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Senior Applied Scientist, Parts Intelligence & Inventory Optimization Canada (Remote) MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 13,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100, the definitive ranking of the top 100 private cloud companies in the world. We're growing fast and hiring the engineering talent to match. We're looking for a Senior Applied Scientist to own the intelligence layer behind our Parts Agent - one of the most strategic bets on our Inventory & EAM roadmap. The agent sits on top of a multi-layer parts data model (PartMaster, StockRecord, PhysicalInstance) and is responsible for answering hard inventory questions: when to reorder, how to optimize stock levels across sites, which parts are at risk of stockout, and how to reconcile messy supplier catalogs into a clean parts master. Your focus will be building the decision models, optimization routines, and AI-powered tools that make those answers trustworthy enough for enterprise maintenance teams to act on. This is a high-ownership role. You'll shape the modeling approach, partner closely with product and design on what inventory managers actually need, and ship iteratively against feedback from real enterprise customers. What you'll do - Own and evolve the optimization and ML models that power Parts Agent capabilities: reorder point prediction, economic order quantity, multi-site stock balancing, and demand forecasting.
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