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Staff Applied Scientist – Distribution Center Solutions
AfreshStaff 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.
Core Competencies
Role fitCore 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
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
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 & technologiesNumpyPandasPython
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.