Sr. Manufacturing Statistics Engineer, Cell Manufacturing

What to Expect

Tesla is re-thinking how batteries are made from the ground up. We are designing new factories, new equipment, new processes, and new software to rapidly scale cell manufacturing. The primary bottleneck to Tesla's future expansion and the transition to sustainable transport and energy storage is our ability to produce and procure batteries - that is why we are innovating in-house, with our collection of world-class engineers, to redefine the industry.

Data, data analytics and analytics automation all play a critical part in this strategy.

As part of the Global Cell Manufacturing Analytics team, you will drive analytics of critical and complex questions around process integration and overall factory optimization. While the role is based at Gigafactory Texas, you will support all of Tesla's cell manufacturing factories across North America and Europe. You will develop data analytics workflows and impact the design of data architecture and software solutions that will be deployed globally.

In this role, you will also develop data-driven models and analyses that will help our leadership ramp up and optimize our cell factories as fast as possible and maximize yield, throughput, and effectiveness.

Your hands-on analytics work will enable various engineering, operations, and executive customers at Tesla to leverage the vast amounts of data generated from the cell manufacturing process all the way to the global Tesla vehicle fleet, to design and produce safer, lower-cost, and higher-performance cells.

The work environment is intellectually demanding, fast paced, and incredibly exciting. You should be ready to push your limits, as you join a highly motivated and capable global team to achieve incredible goals.

• Conduct root cause analysis, correlation studies, DOE, and trial data analysis to resolve battery cell manufacturing issues at Gigafactory Texas, improving yield, quality, efficiency, and process control
• Perform exploratory data analysis, statistical modeling, feature engineering, simulations, and predictive analytics on production data (e.g., sensor logs, time-series, defect metrics) to uncover insights and recommend optimizations
• Build interactive dashboards and visualizations (e.g., using Tableau or Grafana) to share analysis findings, handle ad-hoc requests, and generate reports for engineering and quality teams at GFTX
• Collaborate with cross-functional teams to define analytics needs, integrate insights into workflows, monitor data quality and anomalies, and support sustainable energy goals
• Prototype analytical tools, trainings, and instructions to enable engineers for routine analytics; partner with software teams to product ionize as needed, and contribute to projects enhancing performance, cost, safety, and innovation

• Degree in quantitative discipline (e.g., Computer Science, Mathematics, Statistics, Mechanical/Electrical/Chemical/Industrial Engineering) or equivalent experience
• 4+ years industrial experience preferred (manufacturing, semiconductor, automobiles, pharmaceuticals, engineering, etc.)
• Strong statistical skills for exploratory data analysis, modeling and optimization (Gaussian Processes, Bayesian Optimization), and extracting insights from diverse datasets (e.g., time-series, sensor logs, images)
• Experience with using tools like JMP/Minitab/R/Python for Design of Experiments, Statistical Process Control, correlation studies, root cause analysis, trial evaluation, and quality control
• Industrial experience in domains like semiconductor, automobile, or pharmaceuticals, including process control and optimization methods for high-volume production
• Expertise in visualization tools (e.g., Tableau or Grafana) to create dashboards and communicate findings to varied audiences
• Proficiency in Python, SQL, Pandas, and Num Py for data analytics, modeling, and ETL in industrial settings
• Skills in real-time data processing, anomaly detection, collaboration, and communication for fast-paced manufacturing environments like Gigafactory Texas
• Experience with Git or other source control software
• Experience with advanced ETL/orchestration tools (e.g., Spark, Airflow)…