Samsara

Senior Applied Scientist II, Supply Chain

Samsara

full-time

Posted on:

Origin:  • 🇺🇸 United States

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Salary

💰 $157,675 - $238,500 per year

Job Level

Senior

Tech Stack

AWSAzureCloudERPETLGoogle Cloud PlatformIoTPythonSQLTableau

About the role

  • Design, develop, and deploy advanced machine learning and statistical models that optimize and transform Samsara’s global supply chain.
  • Forecast demand across thousands of SKUs to modeling supply risk using real-time IoT signals.
  • You’ll work alongside data scientists, software engineers, and domain experts, collaborating cross-functionally with teams in Product, Engineering, Procurement, and Finance.
  • You’ll report to the Director of Supply Chain Innovation & Intelligence and play a key role in shaping the team’s roadmap, scientific agenda, and modeling standards.
  • This role is ideal for a deeply technical IC who thrives in ambiguity, thinks strategically, and enjoys end-to-end ownership—from ideation to deployment.
  • This role is open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area.
  • You should apply if: You are motivated by impact; You combine scientific rigor with real-world pragmatism; You want to work on hard problems; You are a self-directed leader; You enjoy building models that matter.
  • In this role, you will: Define the end-to-end AI transformation roadmap for supply chain alongside the Director, aligning with company OKRs and working closely with executive stakeholders.
  • Own the design, training, validation, and deployment of ML and statistical models (e.g., demand forecasting, inventory optimization, supplier risk scoring), ensuring robust MLOps practices and measurable ROI.
  • Build predictive models to forecast demand, lead times, and cellular spend across Samsara’s global supply network.
  • Create novel features using large-scale ERP, IoT, and third-party datasets; build pipelines and ETL jobs to serve models and stakeholders.
  • Deliver production-grade code that supports both batch and real-time inference with MLOps best practices.
  • Act as the AI liaison to Product, Engineering, Procurement, and Finance—ensuring alignment on data requirements, integration, and change management.
  • Drive enhancements to our data infrastructure and analytics platform to support real-time model training, monitoring, and inference at scale.
  • Mentor junior scientists through code reviews and collaborative project work.
  • Act as a key scientific voice in roadmap planning, experimentation frameworks, and modeling strategy discussions.
  • Identify gaps in data, tools, and processes—and lead initiatives to close them.
  • Establish governance frameworks, documentation standards, and quality controls for model development, validation, and lifecycle management.
  • Partner with Ops management to drive adoption of AI tools, define new processes, and train supply chain teams on insights-driven workflows.
  • Hire, develop and lead an inclusive, engaged, and high-performing team.
  • Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.

Requirements

  • 8+ years of experience in applied data science or machine learning, ideally in supply chain, operations research, logistics, or manufacturing.
  • Master’s or PhD in Computer Science, Statistics, Data Science, EE, OR, or a related technical field.
  • Expertise in statistical modeling or machine learning, including time series forecasting, optimization, and anomaly detection.
  • Strong coding skills in Python and SQL; experience developing and deploying production ML systems.
  • Familiarity with MLOps practices, including automated testing, CI/CD, model versioning, and monitoring.
  • Demonstrated track record building real-time inference pipelines and managing GPU/TPU resources.
  • Familiarity with data visualization tools (e.g., Tableau, Power BI) and cloud platforms (e.g., AWS, GCP, or Azure).
  • A passion for operational excellence, cost efficiency, and building scalable, data-driven solutions.
  • Exceptional problem-solving, critical thinking, and communication abilities.