Data Analyst/Data Scientist - (B2)

Role: Data Analyst/Data Scientist - (B2)

Location: Austin, TX (Onsite) or Santa Clara, CA (Onsite)

Who We Are

Applied Materials is the 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 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 work beyond the cutting-edge, continuously pushing the boundaries of science and engineering to make possible the next generations of technology, join us to Make Possible a Better Future.

Key Responsibilities

• Support GIS and Business intelligence, Big Data and AI/ML personnel  that  interface with business unit or function customers for the purpose of business technology alignment, solution discovery, and service management.
• With supervision, analyzes business requirements and/or issues, converts analysis to functional and technical specifications, and assists in the design and technical development of business intelligence, big data and AI/ML solutions to meet business requirements. Perform and document software application and technical platform configuration, prepare and execute test scenarios and scripts (unit, integration, performance, regression, acceptance) and data conversions. May participate in new technology evaluations.
• With minimal supervision, provides Business Intelligence, big data and AI/ML application and platform support services to  meet performance, availability, customer service level agreement, and  customer satisfaction targets. Participates in reviewing and monitoring complex production systems to ensure continuous, effective performance; determines modifications as needed. Performs System analysis and debugging of applications and platforms to identify problem root causes. Completes root cause analysis for incidents and outages. 
• With supervision, Adheres to GIS project management, software application development, testing, service management, change management, RCA  and other relevant processes, standards, governance  and controls. May manage execution of SOX controls and testing, and support internal and external audits. 
• Participates as a Business intelligence, Big Data or AI/ML application or  project team member.  With supervision, may manage small continuous improvement projects  to ensure effective and efficient execution  guardrails of scope, timeline, budget and quality

Qualifications

• Expertise regarding data models, database design development, data mining and segmentation techniques.
• Strong knowledge of and experience with reporting tools (Tableau), databases (SQL etc), programming (R, Python), Databricks/Cloud Data Management.
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests etc.) and experience with applications.
• Strong analytics skill with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
• Knowledge of a variety of machine learning techniques/models (k-means, decision trees, random forest etc.)
• Expertise in writing and reviewing SQL Queries
• Good knowledge in various machine learning

What We Offer

At Applied, we prioritize the well-being of you and your family.  Your happiness, health, and resiliency are at the core of our benefits and wellness programs.  Our robust total rewards package makes it easier to take care of your whole self and your whole family.  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.

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Responsibilities

• Interpret data, analyze results using statistical techniques and provide ongoing reports.
• Develop and implement  data collection systems, data analytics and other strategies that optimize statistical efficiency and quality.
• Develop custom data models and algorithms to apply to data sets.
• Use predictive modelling to solve variety of Business Problems.
• Acquire data from primary or second