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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Statistician - **Company:** Tesla Motors - **Location:** Fremont, CA, United States - **Salary:** $96,000.0 - $144,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Artificial Intelligence, Computer Programming, Continuous Integration, Data Validation, Extract Transform Load (ETL), Django Web Framework, Global Distribution Systems, Monitoring of Systems, Python (Programming Language), Machine Learning, NumPy, Software Tools, Tensorflow, Service-Oriented Architecture, SQL Databases, Digital Twin, Pytorch, ReactJS, Large Language Models, Prompt Engineering, Pandas, Containerization, Scikit Learn, Optimization Algorithms, Machine Learning Operations, Restful APIs, Software Version Control, Docker - **Published:** September 12, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18254894?backUrl=%2Fcareer%2F18254894%2FData-Statistician-California-Fremont ## About the Role * Degree in Data Science, AI, Applied Math or Operations Research, or equivalent experience * Strong foundation in mathematics, algorithms, and optimization techniques * Expertise in large language models, autonomous AI agents, prompt engineering, and modern AI frameworks * Strong programming proficiency in Python and SQL, with experience using libraries such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch * Hands-on experience developing full-stack applications using Django (Python), Java-based services, and React, with a solid understanding of RESTful API design, integration, and service-oriented architectures * Knowledge of MLOps best practices, including CI/CD pipelines, model monitoring, and familiarity with containerization and orchestration tools such as Docker and Kubernetes ## Description We are seeking a highly skilled and driven Data Statistician with software skills to help us develop the next Supply Chain platform with a focus on Inbound analytics, agent development and day-to-day operations. You will be part of the Supply Chain Optimization team that is managing strategic projects and continuous improvement efforts for Tesla's Global Distribution Network. The role requires the ability to build strong cross-functional working relationships with Material Planning, Logistics, Finance, Warehouse Operations and Service Operations teams. You will require a sharp business focus, a collaborative style of working, and a proactive and critical mindset. You need to acquire deep subject matter knowledge about systems, sourcing, planning and fulfillment processes to build models that drive impactful business changes. The role is expected to simultaneously handle multiple projects of department-level scale and global reach. This role is a strong fit for someone early in their career who is eager to build deep operational knowledge and grow into a ML engineering role. What You'll Do * Build and maintain ETL pipelines and recurring analytics to support inbound and service parts operations decision-making * Conduct deep-dive analyses on supply chain performances, including benchmarking, patterns and bottlenecks diagnosis as well as scenario modeling * Develop and integrate Digital Twin capabilities that unify inbound supply, outbound demand, logistics constraints, warehouse capacity, contributing to feedback loops, data validation and platform testing * Architect, own, and operate end-to-end production ML pipelines, including CI/CD, model versioning, and orchestration, to ensure scalable, modular, reliable, and high-performance inventory optimization systems * Design and implement ML models to analyze bottlenecks for Service Parts Operations, specifically on prep performance and diagnosis * Deliver multi-model finance optimizations that integrate cost strategies, simulate disruptions and recommend initiatives to improve overall throughput and productivity while maintaining costs low * Support engagement and efficient integration of Supply Chain tools within the network * Translate complex quantitative results into clear narratives and visualizations, enabling leadership to make informed tradeoffs between inventory investment, service levels, and operational complexity across the global supply chain ## Related Videos - [Industrializing your Data Science capabilities](https://www.wearedevelopers.com/videos/178-industrializing-your-data-science-capabilities) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Vectorize all the things! 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