Sr. Predictive Analytics Engineer - Operational Excellence

Bloom Energy•San Jose, CA

13d•Onsite

About The Position

Bloom Energy is seeking a Sr. Predictive Analytics Engineer for its Operational Excellence team. The role is based in San Jose, California, and is fully on-site in an office. It provides engineering and technical guidance to help achieve reliability, quality, cost, and delivery goals across components, and supports Quality Engineering, Supply Chain Quality, Manufacturing Quality, and PCS Quality teams. The role applies policies and procedures toward zero-defect flow for purchased, contract-manufactured, and Bloom Energy-manufactured parts and materials. The engineer measures and categorizes quality costs using ERP and quality management system data, monitors and tracks Cost of Quality, verifies data accuracy, and works with functional owners on detailed Pareto analyses and root-cause analysis. The position also promotes early failure detection, risk assessment, reliability testing, qualification, continuous improvement, and reduction of poor-quality costs. It leads cross-functional problem-solving efforts and data-driven root-cause failure analyses for design, manufacturing, and administrative problems, while collaborating with internal teams, suppliers, and customers. Bloom Energy describes itself as a clean-energy company whose solid oxide fuel cell and electrolyzer technologies serve critical industries. The company states that it is an equal opportunity employer and makes reasonable accommodations for qualified applicants and employees with disabilities. Compensation is determined in part by relevant skills and experience; the stated salary range is $155,800 to $224,200.

Requirements

10+ years of increasing responsibility in Quality, Manufacturing, and Reliability.
Proven successful application of multidisciplinary engineering problem-solving techniques.
Working knowledge and experience with modern manufacturing Statistical Process Control, including SPC, process capability, Cp, and Cpk.
Strong verbal, active-listening, and written communication skills.
Planning and leadership skills.
Familiarity with metrology, calibration, and Gage R&R.
Experience in Quality System Auditing.
Experience in product phase-gate, NPI, and technology transfer.
Experience applying PPAP and First Article Inspections and reports.
Strong critical thinking, analytical, and problem-solving skills.
Ability to drive material quality improvement through supplier manufacturing processes using incoming and in-process data gathering and analysis.
Ability to work effectively in an intense, dynamic, fast-paced, and demanding work environment.
Proficiency with Microsoft Office Suite and statistical software.
Passion for excellence.
BS, MS, or PhD in Mechanical, Material Science, Chemical, Electrical, or Systems Engineering.

Responsibilities

Provide engineering and technical guidance to promote reliability, quality, cost, and delivery goals for components.
Support the Quality Engineering, Supply Chain Quality, Manufacturing Quality, and PCS Quality teams.
Apply existing policies and procedures to achieve zero-defect flow for purchased, contract-manufactured, and Bloom Energy-manufactured parts and materials.
Measure and categorize quality costs into prevention, appraisal, internal failure, and external failure metrics using ERP and quality management system data.
Drive component and design failures back to the earliest point of detection in the process.
Work with product engineering to teach and perform early-stage risk assessments, including DFMEA, and establish reliability testing programs for components and raw materials to meet life-in-service business plans.
Monitor and track Cost of Quality.
Ensure data accuracy and work with functional owners to break down costs into second-, third-, and fourth-level Pareto analyses with root-cause analysis.
Initiate, support, or lead quality, continuous process improvement, qualification, and cost-of-poor-quality reduction activities.
Lead critical problem-solving task forces, emphasizing cross-functional input, accountability, time to RCCA, and mitigation of at-risk inventory or field units.
Perform data-driven root-cause failure analyses for design, manufacturing, and administrative problems.
Collaborate across departments and with suppliers and customers, building strong working relationships.