ASML US brings together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market and service these advanced machines, which enable our customers - the worlds leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, the Netherlands, and we have 18 office locations around the United States including main offices in Chandler Arizona, San Jose and San Diego California, Wilton Connecticut, and Hillsboro Oregon.
Data Science Organization at ASMLis looking for an experienced Data Scientist who has a passion to build data products and data systems.
The Data Science team began to make the most use of a vast data acquired from our hardware and software products from 2014. As our vision expands, the opportunity to make important contributions to the company and to our customers through data analytics is also expanding. We seek a Principle Data Scientist with practical experience in exploring big data opportunity at ASML.
As a Principal Data Scientist, you will be responsible for utilizing disparate data sources in novel ways, with the aim of generating actionable insights. The insights can create new offerings or improve the capabilities, performance and efficiency of existing products and services throughout the company. Job Description
You will work closely with individual team leads to formulate problem statements and work through the lifecycle of delivering these insights to production. You will design and organize large and complex data sets from varied sources, while thinking strategically about uses of data and issues such as scalability. You will deliver mathematical and statistical models with proven predictive power.
Key Responsibilities / Performance Requirements:Understand existing business flow and product features, dive into the underlying data, apply relevant Data Mining techniques and/or Machine Learning algorithms and propose data analytic product to improve the product intelligence Implement the applicable Machine Learning or statistics based algorithm for prediction and optimization and deliver the trained model to production Design, build and support algorithms of data transformation, conversion, computation on Hadoop and other distributed Big Data Systems
PhD or MSof Computer Science/Engineering/Mathematics or equivalent
Experience Five or more years of relevant experience Excellent understanding (algorithm level) of machine learning, statistics, and optimization Experience with popular data analysis and machine learning libraries (sklearn, TensorFlow, H2O, MLlib, etc.) Familiar with Hadoop ecosystem and good understanding about its key components (HDFS, Hive, Pig, Spark, etc.) Hands-on experience on data analysis, machine learning modeling, and data visualization with large scale dataset in Hadoop system using Hive, Spark, MLlib, etc. Hands-on experience with different database architectures (SQL, NoSQL, Hive, HBase, etc.) Extensive knowledge of at least one scientific or statistical programming language such as Matlab, R or Python (must include SciPy, NumPy, Pandas) Prior work and/or research demonstrates experience in the following areas: data mining, pattern discovery, anomaly detection, root cause analysis
Desired: Experience in deep learning Experience with different tools in Hadoop system (Zepplin, Jupyter, Storm, Sqoop, Flume, Ambari, etc.) Proficient in one or two of the languages: Java, Python, C++, Scala in Linux/Unix
Personal skills Strong verbal and written communication skills Ability to articulate at a system level Desire and ability to work well with others in a team environment.
Context of the position
This position primarily works in an office environment. It requires frequent sitting, standing and walking. Daily use of a computer is required. May stand for extended periods when facilitating meetings. The physical demands of the position described herein are essential functions of the job and employees must be able to successfully perform these tasks for extended periods. Reasonable accommodations may be made for those individuals with real or perceived disabilities to perform the essential functions of the job described.