Systems Analytics Engineer/Applied Scientist

　　Applied Materials, Inc. is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. Our expertise in modifying materials at atomic levels and on an industrial scale enables customers to transform possibilities into reality. At Applied Materials, our innovations make possible the technology shaping the future.

　　Key Responsibilities and Requirements:

　　Problem identification and troubleshooting using analytics a variety of difficult engineering problems in field of technical expertise, including serviceability and manufacturability. Works in project teams as subject matter expert to design and develop program methods to consolidate and analyze structured and unstructured, diverse 'big data' sources – eg. sensor and metrology data. Identify data sources and automate collection processes.

　　Performs statistical and data-mining analysis, using statistical tools like R, Julia, and MATLAB; input and design of data acquisition systems, data structure and database design. Interfaces with internal customers for requirements analysis and compiles data for scheduled or special reports and analysis Works in project teams to develop analytical models, algorithms and automated processes, applying SQL understanding and PHP or Python programming, to cleanse, integrate and evaluate large datasets. Analyze large amounts of information to discover trends and patterns Build predictive models and machine-learning algorithms Supports the timely development of products for manufacturing and process information by applying sophisticated data analytics, understands the business data gathering processes of the business Support system engineering projects that have a substantial mix of electrical, mechanical, physics, algorithms and software design, and understand the underlying system implications.

　　Provide remote support to field personnel as required and if needed. Demonstrated experience applying data science methods to real-world data problems

　　Requirements

　　Master’s or PhD program in Computer Science, Data Science, Industrial Engg, EE, Physics, or a related field

　　Student must be in good academic standing at their university, with a GPA of 3.0 or above on a 4.0 scale

　　Proficiency in Python, R, and MATLAB,

　　Deep Learning concepts and frameworks – expertise programming in Python data stack, including ML packages such as Scikit-Learn, Tensorflow, Keras, and pyTorch

　　Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)

　　Desired Skills – Great to Have!

　　Experience in the fields of quantitative causal inference and counterfactual reasoning, causal reinforcement learning, and the intersection of causal inference and machine learning/reasoning (including computer vision, natural language processing). Process and gain insight from large amounts of multimodal relational data (e.g. time-series, text, images, graphs, spatio-temporal processes).

　　Proficiency in one or two of the FE frameworks: JavaScript (Angular), JQuery, XML, Bokeh, pyQT, React

　　Functional Knowledge

　　Demonstrates conceptual and practical expertise in own discipline and basic knowledge of related disciplines

　　Problem Solving

　　Solves complex problems; takes a new perspective on existing solutions; exercises judgment based on the analysis of multiple sources of information

　　Impact

　　Impacts a range of customer, operational, project or service activities within own team and other related teams; works within broad guidelines and policies

　　Interpersonal Skills

　　Explains difficult or sensitive information; works to build consensus

　　Applied Materials is committed to diversity in its workforce including Equal Employment Opportunity for Minorities, Females, Protected Veterans and Individuals with Disabilities.

　　Applied Materials is the leader in materials engineering solutions to produce virtually every new chip and advanced display in the world. Our expertise in modifying materials at atomic levels and on an industrial scale enables customers to transform possibilities into reality. Our innovations make possible the technology shaping the future. To achieve this, we employ some of the best, brightest, and most talented people in the world who work together as part of a winning team.

　　While virtually every nationality, culture, and background are currently represented within Applied Materials, we strive for a more robust Culture of Inclusion (COI) and diversity. Leveraging our COI vision helps drive innovation, build organizational capabilities, create equal opportunities for everyone, and achieve our companys definition of Winning.

　　We are actively recruiting a Systems Analytics Engineer!

　　Position Overview

　　Are you inspired by how data analytics can be used to diagnose, improve and add value to hardware? Are you a natural team player who loves to solve complex problems? If yes, then youll fit right in here at Applied Materials.

　　We are a fast-growing team of doers who are bringing domain knowledge-aided data analytics to our semiconductor equipment. We are working passionately to transform our customers experiences in ground-breaking ways new to this industry. We will give you the guidance, tools and support you need on this journey with us that is rewarding, fulfilling and fun!

　　We are seeking a talented individual with general expertise and demonstrated achievement in hardware analytics, systems engineering and data science. You will be a member of the Analytics Team that is responsible for developing data-driven analytics solutions to optimize semiconductor manufacturing. Your work will involve developing tools to collect, analyze, and visualize diverse data sets to address a variety of high value engineering issues. These tools will then be used to enhance hardware performance for both internal and external customers.

　　The ideal candidate should be comfortable working cross-functionally as well as delivering results independently. The position requires willingness to learn new technologies, solving complex problems, identifying innovative solutions and troubleshooting.

　　Job Responsibilities

　　Develop and implement analytics-driven optimization through deployment of software and/or algorithms

　　Serve as a technical lead for highly cross-functional internal R&D initiatives

　　Drive product enhancements with both classical engineering and data science techniques

　　Champion new ML/AI based optimization techniques across the organization

　　Fine tune application performance, troubleshoot and resolve data processing issues

　　Provide end-to-end solution for a given problem and effectively communicate solutions to the team

　　Thrive in a dynamic, multi-team fast-paced, rapid development, startup-like environment as well as work independently

　　Minimum Qualifications

　　1-3 years of demonstrated achievement with hardware-oriented analytics

　　Hardware or process engineering experience in semiconductor manufacturing or similar field

　　Degree in quantitative field (e.g. Computer Science, Engineering, Statistics, Chemical Engineering, Mechanical Engineering, Electrical Engineering)

　　Understanding of physical systems (e.g. signals processing, sensors, semiconductors, manufacturing, microfluidics)

　　Experience with machine learning or other statistical data analysis techniques, such as regression, time series analysis, hypothesis testing, classification, or clustering

　　Experience performing data extraction, cleaning, analysis, and visualization for medium to large datasets

　　Experience with at least one programming language (Python, R, Java, etc.) and writing SQL queries

　　Experience with scientific computing packages such as scikit-learn, numpy, SciPy, pandas, dplyr, or ggplot2

　　Company Facts:

　　Ticker: Nasdaq: AMAT

　　Fiscal 2020 Revenue: $17.2 billion

　　Fiscal 2020 R&D: $2.2 billion

　　Founded: November 10, 1967

　　Headquarters: Santa Clara, California

　　Global Presence: 93 locations in 17 countries

　　Manufacturing: China, Germany, Israel, Italy, Singapore, Taiwan, United States

　　Employees: 24,000 worldwide

　　Patents: 14,300 issued

　　Applied Materials closed fiscal 2020 with record quarterly performance as demand for our semiconductor systems and services remains very strong, said Gary Dickerson, president and CEO. Our future opportunities have never looked better and, as powerful technology trends take shape, we are uniquely positioned to accelerate our customers roadmaps and outperform our markets.

　　Applied Materials is an Equal Opportunity Employer committed to diversity in its workforce.

　　#LI

　　Qualifications / Education:

　　Master’s or PhD program in Computer Science, Data Science, Industrial Engg, EE, Physics, or a related field

　　Skills

　　Proficiency in Python, R, and MATLAB,

　　Deep Learning concepts and frameworks – expertise programming in Python data stack, including ML packages such as Scikit-Learn, Tensorflow, Keras, and pyTorch

　　Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)

　　Years of Experience:

　　4 - 7 Years

　　Work Experience:

　　Additional Information

　　Travel:

　　Yes, 20% of the Time

　　Relocation Eligible:

　　Yes

　　Qualifications

　　Education:

　　Bachelor's Degree

　　Skills:

　　Certifications:

　　Languages:

　　Years of Experience:

　　4 - 7 Years

　　Work Experience:

　　Additional Information

　　Time Type:

　　Full time

　　Employee Type:

　　Assignee / Regular

　　Travel:

　　Yes, 10% of the Time

　　Relocation Eligible:

　　Yes

　　Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.