Senior Applied Scientist II, Supply Chain

About the role:

We are seeking a Senior Applied Scientist II to join our Supply Chain Innovation & Intelligence this role youll 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 youll apply cutting-edge techniques to solve complex problems with direct business impact.

Youll work alongside data scientists software engineers and domain experts collaborating cross-functionally with teams in Product Engineering Procurement and Finance. Youll report to the Director of Supply Chain Innovation & Intelligence and play a key role in shaping the teams 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 ownershipfrom 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 Samsaras operations.
• You combine scientific rigor with real-world pragmatism: Youre skilled at navigating trade-offs between model complexity performance and maintainability.
• You want to work on hard problems: Youll 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 Samsaras 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 Financeensuring 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 processesand 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 Samsaras 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.

Minimum requirements for the role:

• 8 years of experience in applied data science or machine learning ideally in supply chain operations research logistics or manufacturing.
• Masters 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 fluency in 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.

An ideal candidate also has:

• Deep Statistical Expertise: Able to design and validate experiments (A/B multi-armed bandits) and apply Bayesian methods for uncertainty quantification.
• Time-Series Mastery: Proven track record building advanced forecasting models (e.g. Prophet LSTMs Transformer-based) for intermittent demand and seasonal patterns.
• Cost Optimization Mindset: Skilled in profiling ML workloads and driving down cloud/GPU spend through model compression (quantization pruning) and serverless architectures.
• Cross-Region Scaling: Demonstrated ability to deploy low-latency inference across multiple geographic regions with fail-over and disaster-recovery strategies.
• Vendor & Open-Source Savvy: Experience evaluating and integrating third-party ML platforms and contributing to or leveraging relevant open-source projects.

Required Experience:

Senior IC