Software Engineer / Data Scientist New College Grad- Bachelor's (Gloucester, MA)

Applied Materials is looking for a Software Engineering / Data Scientist to engage in the development of software to aid in the extraction of valuable technical and business insights from our semiconductor manufacturing tools.  This work will utilize tool telemetry modeling and business analytics for prediction in our Service Products business unit.

Applied Materials is the 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 helps our customers – who make smartphones, supercomputers, virtual reality headsets, autonomous vehicles and more – transform their ideas into reality. Our innovations Make Possible® a Better Future.

Inside our company, we apply the idea of make possible as we work together. We value our people and teams who turn possibilities into reality by advancing our strategy, accomplishing great things and empowering others. We are deeply committed to fostering a Culture of Inclusion where every person knows they belong, feels empowered to bring their whole self to work, and is inspired to grow. We are looking for candidates that bring their problem-solving passion to enable us to deliver these solutions to our customers.

This role will focus on analytics for both business and tool modeling from multivariate semiconductor manufacturing tool telemetry and other data to predict market, business impacts, process outcomes, and tool failures. The telemetry data will be mined, and models developed to identify correlations between operation and outcomes, enabling prediction of faults and performance trends.  This can inform existing and future products that deliver customer solutions.

Candidates should be highly analytical with a passion for problem-solving, software development, math and statistics without losing sight of the business implications. Critical thinking and systematic skills are essential for interpreting data and understanding how this can be applied to our products.  The role is interdisciplinary supporting many aspects of the business, and while focused on solution development, flexibility is a key characteristic as new challenges and tasks present themselves.

Your goal will be to help our company make better decisions and to uncover the hidden gems in the data that will empower our products to be successful.  You should be well versed in supervised and unsupervised learning technique, time series analysis, statistics, and probability.  Ideally, knowledge of electrical circuits, scientific methods and processes, and a willingness to learn the physics underlying the tools.  Bringing these capabilities to collecting, analyzing, and modeling of multiple and varied data sets. From these data-driven insights, the candidate would develop machine learning algorithms to help solve technical challenges.

Applied Material's Ion Implant tools use a range of physics, scientific and engineering techniques to achieve their outcomes, these include the ion beams, plasma, high voltage, electrostatic steering and focusing, electromagnets, high vacuum, robots, and control systems.  The telemetry from the tools come from the settings for the control of these various systems as well as sensors to monitor them. 

Team Overview

The Implant SBU Data Science Team is a collaborative team of Data Scientists, Software and Computer Engineers and Business Experience that work on internal and go to market solutions. The team has a range of backgrounds and experiences including MS ADS, MBA and other degrees and certificates and we encourage ongoing learning and personal development. Being a small team everyone has niches for contribution. The team balances different backgrounds to bring a richer perspective to the whole and the wider group works routinely with our teammates in all of the Applied regions. We are located on the Gloucester, Massachusetts campus.

Key Responsibilities

• Develop Software for Scientific and Business Applications within the Data Science Team.
• Understand complex problems and find and develop the software and analytics needed to model, predict, and address them in collaboration with others.
• Use Statistics to measure and quantify the data and solutions as well as inform Design of Experiments.
• Work with existing frameworks and well as add to the team’s repertoire of Machine Learning capabilities and then develop and deploy solutions based on this work to the market in conjunction with the broader team.
• Support the goals of the team to help deliver analysis for better decision making
• Sometimes business implications may require consideration of data from multiple sources both technical and business to facilitate a solution<