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Data Scientist I

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Location: Hillsboro, Oregon, United States
Job ID: 45136
Date Posted: Feb 21, 2020
Segment: High-Tech
Business Unit: Hitachi High-Technologies
Company Name: Hitachi High Technologies America, Inc.
Profession (Job Category): Engineering
Job Type (Experience Level): Experienced
Job Schedule: Full-time
Remote: No

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Description

GENERAL DESCRIPTION


The Data Scientist I (DS) position supports the business objectives of HTA’s Semiconductor Equipment Division (SED) related to sales of Reactive Ion Etch (RIE) or Plasma Etch (PE) equipment to the semiconductor industry.   The position's main objective is to design, develop, and program systems to consolidate and analyze etcher and etching related diverse and unstructured “big data” sources.  The DS generates actionable insights and solutions in support of HTA’s process development and process engineering teams.  



PRIMARY RESPONSIBILITIES


Interacts with process engineering teams to identify questions and issues for data analysis and experiments.  

Define data structures, evaluate data quality, and perform appropriate data analyses using relevant software.  

Develop and code software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. 

Identify, interpret, and communicate meaningful insights, conclusions, and analysis to engineering, research teams, and business managers.  

Understand and contribute to statistical, machine learning, and first-principle modeling projects focusing on semiconductor processes. 

Translate technical questions into actionable experimental designs.

Process development tasks with support from the process engineering team

Generate internal and external documentation for products, presentations, and technical reports for review by relevant stakeholders. 

Other duties as required

Qualifications

 EDUCATION, LICENSES, AND/OR CERTIFICATION REQUIREMENTS

M.S. or Ph.D. in mathematics, statistics, physics, chemistry, computer science, electrical engineering, chemical engineering, or material science or an equivalent combination of education and experience


EXPERIENCE AND TRAVEL REQUIREMENTS

Two years of hands on hypothesis driven data analysis and statistics experience
Two years of machine learning or exploratory data analysis related experience preferred
Recurrent neural network, convolutional neural network, and graphic processing unit (GPU) experience preferred
Must be willing to travel domestically and internationally approximately 5% of the time including assignments that require multiple weeks stay
Must be willing to live abroad on international assignments that typically last three months’ time or less


KNOWLEDGE, SKILLS, and/or ABILITIES REQUIREMENTS

Knowledge of statistical methods for modeling multivariate data sets including machine learning techniques.
Develop deep learning networks for physical systems and knowledge of wafer processing technology. 
Strong general technical knowledge of semiconductor wafer processing. 
Strong knowledge of programming environments such as Matlab, R, Python, SAS, or equivalent systems/programs.
Strong engineering analytical and problem solving skills
Understanding of scientific methods
Self-motivated and ability to adapt to changes in a fast moving environment.
Ability to take R&D initiative and deliver tangible results under deadlines.
Ability to work independently and inquisitively with minimal direction.
Knowledge of design of experiments (DOE).
Excellent teamwork and customer focus.  
Flexibility to work across all functions/levels as part of a team.
Candidate must have excellent verbal and written communication skills with the ability to effectively communicate technical analyses and results.
Ability to work in a clean room environment for extended hours. 
Strong computer skills including Microsoft Office software competency.
Knowledge of PE process experience or semiconductor processing preferred

 


  
 

Equal Opportunity Employer (EOE) – Females/Minorities/Protected Veterans/Individuals with Disabilities

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