We are seeking a
Sr. Staff Process Data Scientist to join our Data Science team, where you will apply deep chemical engineering expertise alongside coding, analytics, and automation to improve, scale, and optimize complex manufacturing processes.
This role sits at the intersection of process engineering, data science, and software, focusing on building scalable, data-driven solutions rather than day-to-day operations.This role will report to Sr. Principal Engineer, Data Science and is based in
San Jose, CA.This is a fully on-site, in office role 5 days a week.Key Responsibilities- Design and develop Python-based tools, pipelines, and automated workflows for engineering analysis
- Build, deploy, and maintain digital twins, soft sensors, and advanced analytics models for process optimization
- Analyze large-scale manufacturing datasets (including time-series and historian data) to identify opportunities in yield, throughput, and reliability
- Partner cross-functionally with process engineers, data scientists, and software engineers to operationalize solutions in production environments
- Translate complex process engineering challenges into scalable data models and software implementations
- Own ambiguous, high-impact problems and drive them from model concept through validation, deployment, and monitoring
Required Qualifications- MS or PhD in Chemical Engineering, Mechanical Engineering, Electrical Engineering, or a related field in the physical sciences (e.g., Physics, Chemistry, Applied Mathematics)
- 6+ years of industry experience, with demonstrated impact at a senior or staff level in industrial, manufacturing, or process-oriented environments
- Strong ability to translate physical systems and engineering/scientific problems into data-driven models and production-grade code
- Solid foundation in first principles, physical systems, and process understanding, with the ability to connect theory to real-world applications
- Experience working with complex systems involving sensors, instrumentation, or process data
Core Skills- Process modeling & engineering fundamentals
- First-principles modeling, scale-up, and root-cause analysis
- Programming & data analysis
- Python (NumPy, Pandas, SciPy, visualization libraries)
- Automation of engineering calculations and analytical workflows
- Data engineering & analytics
- Large-scale datasets, time-series analysis, and process historian data
- Machine learning for physical systems
- Statistical modeling, hybrid modeling (physics + ML), or ML applied to process optimization
- Problem-solving & ownership
- Ability to operate in ambiguous environments and deliver end-to-end solutions
Nice-to-Have (Optional but Valuable)- Experience with digital twin platforms or industrial AI frameworks
- Familiarity with cloud environments (Azure, AWS, or GCP) and MLOps pipelines
- Experience deploying models into real-time or near real-time production systems
- Knowledge of semiconductor, chemicals, energy, or advanced manufacturing processes
Bloom Energy is committed to fair and equitable compensation practices. The total compensation for this position includes standard company benefits and is based on various factors including, but not limited to, relevant skills and experience.
#LI-BC1Salary Ranges:$151,700.00 - $218,300.00
