Staff Applied Scientist

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Develop a comprehensive AI transformation roadmap for the supply chain in collaboration with the Senior Director of Supply Chain AI Transformation, ensuring alignment with company OKRs and executive stakeholders.

• Design, train, validate, and implement production ML models for demand forecasting, inventory optimization, supplier risk evaluation, cellular expenditure prediction, and hardware cash flow management.

• Construct predictive models to forecast demand, inventory levels, lead times, and spending across the global supply network.

• Generate features from extensive ERP, IoT, and third-party datasets and create pipelines and ETL jobs.

• Provide production-ready code that supports both batch and real-time inference while adhering to MLOps best practices.

• Act as the AI liaison for Product, Engineering, Procurement, and Finance teams.

• Improve data infrastructure and analytics platforms to enable real-time model training, monitoring, and inference at scale.

• Mentor junior scientists through code reviews and collaborative project efforts.

• Represent a scientific perspective in roadmap planning, experimentation frameworks, and modeling strategies.

• Identify deficiencies in data, tools, and processes, leading initiatives to address them.

• Establish governance frameworks, documentation standards, and quality controls for model development, validation, and lifecycle management.

• Collaborate with Operations management to promote AI adoption, define processes, and train supply chain teams.

• Advocate for Samsara's cultural principles as the company expands globally.

⛳️ Requirements

• Over 8 years of experience in applied data science or machine learning, preferably in supply chain, operations research, logistics, or manufacturing.

• Master's or PhD in Computer Science, Statistics, Data Science, Electrical Engineering, Operations Research, or a related technical discipline.

• Proficiency in statistical modeling and machine learning, including time series forecasting, optimization, anomaly detection, and causal inference.

• Strong skills in Python programming and fluency in SQL.

• Demonstrated experience in developing and deploying production ML systems.

• Expertise in MLOps practices such as automated testing, CI/CD, model versioning, monitoring, and performance tracking.

• Experience in constructing real-time inference pipelines and managing GPU/TPU resources for large-scale training.

• Familiarity with Tableau, Power BI, and cloud platforms like AWS, GCP, and Azure.

• A passion for operational excellence, cost efficiency, and scalable solutions.

• Proven history of taking products or systems from inception to launch.

• Excellent problem-solving, critical thinking, and communication abilities.

• Proven track record of cross-functional collaboration and promoting the adoption of data-driven solutions.

• Ability to design and validate A/B tests and multi-armed bandits, applying Bayesian methods for quantifying uncertainty.

• Experience in developing advanced forecasting models such as Prophet, LSTMs, or Transformer-based architectures.

• Knowledge of model compression techniques, including quantization and pruning, and serverless architectures.

• Capability to deploy low-latency inference across multiple geographic regions with failover and disaster recovery strategies.

• Experience in evaluating and integrating third-party ML platforms and relevant open-source projects.

• In-depth understanding of supply chain concepts including S&OP, IBP, safety stock, and EOQ.

• Familiarity with ERP systems such as SAP, NetSuite, E2DP, and Propel.

• Preferred background in consumer electronics or B2B hardware manufacturing.

🏝️ Benefits

• Initial RSU grant with no vesting cliff.

• Continuous equity refresh opportunities based on performance.

• Performance-driven bonus or variable pay.

• Flexible, employee-directed remote work model.

• Professional development stipend.

• Comprehensive health care plans.

• Parental leave programs.

• Above-market total compensation package.

• Options for remote, hybrid, and in-person work depending on role and operational needs.