Senior Applied Scientist II, Supply Chain

Who we are

Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale.

Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, Equipment Monitoring, and Site Visibility. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term.

About the role:

We are seeking a Senior Applied Scientist II to join our Supply Chain Innovation & Intelligence team. In this role, you’ll be responsible for designing, developing, and deploying advanced machine learning and statistical models that optimize and transform our global supply chain. From forecasting demand across thousands of SKUs to modeling supply risk using real-time IoT signals, you’ll apply cutting-edge techniques to solve complex problems with direct business impact.

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: Your work will drive smarter, faster, and more sustainable supply chain decisions across Samsara’s operations.
• You combine scientific rigor with real-world pragmatism: You’re skilled at navigating trade-offs between model complexity, performance, and maintainability.
• You want to work on hard problems: You’ll help tackle forecasting volatility, cost optimization, anomaly detection, and more using large, noisy, high-dimensional datasets. 
• You are a self-directed leader: You identify analytical white space, set multi-quarter plans, and mentor others through influence.
• You enjoy building models that matter: Your solutions will be deployed in production, drive decisions, and be regularly evaluated against business KPIs.

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, defi