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发帖数: 45 | 1 【 以下文字转载自 DataSciences 讨论区 】
发信人: tarn (空心), 信区: DataSciences
标 题: Intel Dalian Sr. Data Scientist Position (转载)
发信站: BBS 未名空间站 (Sat Apr 7 19:49:14 2018, 美东)
发信人: tarn (空心), 信区: JobHunting
标 题: Intel Dalian Sr. Data Scientist Position
发信站: BBS 未名空间站 (Sat Apr 7 19:46:52 2018, 美东)
Job Description
Intel Dalian Fab68 site will produce its latest 3D NAND technology. Fab68
has been in operation since 2010 producing 65-nanometer products for Intel.
The collaboration with the Dalian government has been and continues to be an
excellent partnership. We have a long term plan for this facility and may
invest up to $5.5 billion over the coming years to transition this site to
support leading-edge non-volatile Memory production.
This Data Scientist role is an exciting opportunity to apply your knowledge
to translating Fab data into meaningful insights to help solve factory yield
/process engineering problems. In this position, you are expected to deliver
data analysis tools/methodologies for engineers in different areas:
- help them to do quick and efficient signal detection for yield or process
issues;
- improve yield & quality and reduce cost to meet Fab68 Quality/Output/Cost
goals.
The successful candidate will work closely with diverse yield/process
engineers to understand their business needs, analysis methodologies and
come up with solutions to assist in data-driven decisions in their daily
work.
Qualifications and Preferred Experiences:
- Experience using data analysis techniques like predictive modelling,
pattern/machine learning algorithms, clustering, dimensionality reduction,
anomaly detection etc..
- Must have at least one data programming language/scripting experience (e.g
. JMP, R, Python etc.)
- Must be a team worker with excellent communication, presentation, and time
management skills.
- Excellent technical problem solving and analysis skills, ability to
quickly digest complex problems
- Experience with SQL, Hadoop, Spark is a plus
- Experience in semiconductor industry is a plus
- Candidates need to hold at least a Master degree in Statistics, Machine
learning, Computer Science or relevant disciplines. Ph.D is preferred.
If you are interested, please send email to [email protected] |
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