Data Scientist

## Data Scientist Apply locations:
Santa Clara,CAtime type:
Full time posted on:
Posted Todayjob requisition :
R2624867
** Who We Are
** Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT.

If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.
** What We Offer
** Salary:$ - $

Location:

Santa Clara,CAYou’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.
** Job Description
** Be a part of internal consulting team with high visibility to Applied Global Services executive leadership. Lead strategic projects to streamline business processes, improve supply chain and operations, reduce costs, and improve business performance. Have responsibility for complete project life cycle starting with analysis of the as-is process, identification and quantification of the opportunities, development of improvement streams, securing buy-in from stakeholders, and driving implementation.

High impact role that requires relentless change management motivation rewarded with material impact to business unit performance. Opportunity to impact a $6B business with thousands of field engineers, complex global logistics network, and a wide range of products and services.
** Key Responsibilities
*** Structure and break down complex business problems, develop hypothesis, drive analysis and deliver recommendations in a data-driven manner
* Lead thoughtful and rigorous analysis across large data sets and synthesize insights and opportunities
* Work collaboratively across a cross-functional set of stakeholders to gather the right information, pressure test your hypothesis, co-create deliverables, accelerate execution and unlock value
* Optimize operations and business processes to improve performance, reduce cycle time, and shrink costs
* Collect data from multiple sources, filter anomalies, and clean unstructured data to ensure accuracy
* Use statistical data analysis and tools to identify, analyze, and interpret patterns and trends in complex data sets and build diagnosis and prediction models
* Devise and utilize algorithms and models to mine big data stores, perform data and error analysis to improve models, and clean and validate data for accuracy and efficacy
* Create effective Power BI based mockups, prototype, reports, and applications utilizing best practices
* Communicate analytic solutions to stakeholders and implement improvements as needed to operationalize systems
* Create Training Materials and administer end-user training using generative AI models and tools.
* Design, develop and deploy interactive data visualizations using Power BI
* Maintain data systems and assist in developing automated processes for continuous data collection.
** Key Requirements
*** Broad understanding and experience including logistics, financial reporting, purchasing, and service business management.
* Strong analytical skills – able to extract real insight from multiple data sources
* Experience using statistical computer languages (Python, SQL, etc.) to manipulate data and draw insights from large data sets.
* Knowledge of machine learning techniques (clustering, decision tree learning, neural…