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Afresh

Staff Applied Scientist – Distribution Center Solutions

Afresh

Staff Applied Scientist at Afresh managing AI/ML models for fresh inventory control. Solving complex replenishment challenges to minimize food waste and enhance grocery decision-making.

Posted 7/1/2026full-timeRemote • 🇨🇦 CanadaLead💰 CA$169,000 - CA$252,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and implementing AI/ML models for replenishment technology, with a strong focus on inventory optimization and supply chain management. Capable of mentoring teams and communicating complex concepts effectively to diverse stakeholders.

Highest-signal resume keywords
AI/ML Model DevelopmentInventory OptimizationSupply Chain ManagementPython Data StackMentorship

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Operations ResearchStochastic OptimizationApproximate Dynamic ProgrammingDecision AnalysisGame TheoryForecastingNetwork OptimizationComplex Problem SolvingSoftware ImplementationExperimental Rigor
Soft Skills
Excellent CommunicationPresentation Skills
Tools & Technologies
PythonNumpyTorchPandas
Industry Keywords
Large-Scale Decision MakingPerishabilityMulti-Echelon Supply ChainsResearch and DevelopmentTechnical Standards

Tech Stack

Tools & technologies
NumpyPandasPython

About the role

Key responsibilities & impact
  • Lead R&D work at Afresh for the development and performance of AI/ML models that power replenishment technology.
  • Model consumer demand, item-level perishability, and complex multi-echelon supply chains.
  • Drive fundamental changes to the core system from research through production, writing rigorously tested and scalable code.
  • Raise the technical bar across the Intelligence team: mentor scientists and engineers, set standards for experimental rigor, and review designs and results.
  • Push the boundaries of AI capabilities in both products and scientist workflows.

Requirements

What you’ll need
  • MS or PhD in Operations Research, Industrial Engineering, Computer Science, Electrical Engineering, or another quantitative field, or equivalent practical experience.
  • For candidates with an MS, 8+ years of industry experience; for candidates with a PhD, 4+ years of industry experience.
  • Experience researching and building systems that support large-scale decision making under uncertainty.
  • Prior experience in areas such as inventory optimization, supply chain management, network optimization, forecasting, game theory, decision analysis, stochastic optimization, approximate dynamic programming, or related fields is a plus.
  • Excellent communication and presentation skills. You should be able to explain complex mathematical ideas to product teams in plain English and easily translate business requirements into constrained optimization problems.
  • Ability to independently deliver high quality software implementations of your solutions in the Python data stack (numpy/torch/pandas/etc). Prior experience with Python is not required.
  • Nice to Have skills: understanding of ML Platform and a passion for mentorship.

Benefits

Comp & perks
  • Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh.
  • Dedicated mental health support and counseling services.
  • Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
  • Home office stipend and 'Coworking Wallets' for flexible workspace access.
  • Annual professional development budget to master new skills and grow your career at Afresh.
  • Monthly stipends for 'Betterment' (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
  • Flexible paid time off to take the time you need to recharge.