Data Systems Analyst
NVIDIA
Data Systems Analyst
NVIDIA
Designs the chips and software that power AI
Are you passionate about bridging the gap between manufacturing operations and data analytics? At NVIDIA, we’re on the lookout for an ambitious and dedicated Data Systems Analyst to join our SCBT Operations Data Platform DataOps organization in Hsinchu City, Taiwan. As part of a world-class team, you'll drive operational excellence and ensure detailed data integrity across our manufacturing processes. This is your chance to create a significant impact on our supply chain performance and contribute to NVIDIA’s groundbreaking innovations!
What you'll be doing:
Drivebusinessinsightstoenhancemanufacturingefficiency,operationalexecution,andsupplychainperformance.
Enableandmonitorshop-floordatacollectionfornewandexistingcontractmanufacturersandsuppliers.
Identifygapsinoperationalprocessesandrecommendimprovementstoensureseamlessmanufacturingoperations.
Establishandmaintaindataqualityattributesandmetrics,ensuringdataintegrityacrossmanufacturingoperations.
Auditmanufacturingdataquality,addressanomalies,andimplementvalidationprocessesforgreateraccuracyandvisibility.
Collaboratewithexternalpartnersandinternalengineeringteamstoresolveproductiondatadiscrepanciesandsupportproductimplementationrequirements.
Manageproductionconfigurationinformation,maintainingintegrityofmanufacturingattributes,componentrelationships,andproductstructures.
PartnerwithIT,planning,andengineeringteamstotranslateoperationalrequirementsintoscalablesolutionsandsupportcontinuousimprovementinitiatives.
What we need to see:
Bachelor’s or Master’s degree in Industrial Engineering, Supply Chain Management, Information Systems, Computer Science, or equivalent practical experience.
5+ years of experience in electronics manufacturing operations, outsourced manufacturing, supply chain, or related fields.
Strong knowledge of hardware manufacturing processes, product assembly flows, and outsourced manufacturing operations.
Experience with Shop Floor Control Systems (SFCS), Shop Floor Control Systems (SFCS), Manufacturing Execution Systems (MES), Engineering Change Order (ECO) processes, Product Lifecycle Management(PLM), product configuration management, and BOM structures.
Basic to intermediate SQL skills for manufacturing data queries, validation, troubleshooting, and analysis.
Ability to leverage AI-assisted tools and modern technologies to improve operational efficiency and support data-driven decisions.
Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
Self-motivated and detail-oriented, with sound judgment and the ability to work independently in a fast-paced environment, to collaborate effectively with engineering teams, business collaborators, and external manufacturing partners.
Ways to stand out from the crowd:
Experience with manufacturing operations and supply chain management.
Knowledge of manufacturing operational processes covering components, boards, systems, and server products.
Proficiency in writing and optimizing complex SQL queries for manufacturing analytics and operational reporting.
Experience with scripting or programming languages such as Python or Java for automation and data processing, crafting dashboards and reports using Tableau, Power BI, or similar visualization platforms.
Familiarity with systems administration, virtual machines, cloud platforms (AWS, Azure), and data pipeline concepts.
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
#LI-Hybrid
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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