Internship; Data Analytics

Job Title

Internship; Data Analytics

Degree:

Bachelor, Master

Work Experience:

N/A

Travel:

No

Workplace Types:

Hybrid

Job Description:

Introduction to the job

We are seeking a motivated and detail-oriented individual for an internship position focused on analyzing machine logs to derive status overviews and contribute to industrialization improvements. The candidate will work closely with our team to extract valuable insights from machine-generated data, aiming to enhance operational efficiency and identify areas for optimization within our industrial processes.

This position requires access to controlled technology, as defined in the Export Administration Regulations (15 C.F.R. § 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

Role and responsibilities

RAISE stands for Reactive Analysis & Identification of Software Errors, this is a process/framework that by capturing event logs of specific machine tests we can create a status overview for industrialization improvement purposes.

In other words, we can quantify the problems impacting machine tests and provide improvement ideas to prevent future issues.

1. Machine Log Analysis:
Assist in collecting, parsing, and analyzing machine-generated logs to understand operational status and performance.
Gain proficiency in log analysis tools and techniques to extract relevant information from data streams.

2. Status Overview Creation:
Work collaboratively with the team to develop summaries and visual representations of machine status and performance.
Help in creating dashboards or reports that provide an overview of machine operations and identify key trends.

3. Data Validation and Quality Assurance:
Support in verifying the accuracy and integrity of machine log data through validation and quality assurance processes.
Assist in identifying and resolving discrepancies or inconsistencies in the data.

4. Insights and Recommendations:
Aid in interpreting data insights to identify potential areas for improvement in industrial processes.
Contribute ideas and suggestions based on data analysis to enhance operational efficiency and productivity.

5. Documentation and Reporting:
Assist in documenting analysis methodologies, findings, and recommendations in reports or presentations.
Help in formatting and visualizing data for clear and concise reporting purposes.

Education and experience

Univerity/College Student

Pursuing a Bachelor’s degree in Data Science, Computer Science, Engineering, or a related field. Students from diverse backgrounds are encouraged to apply.
 

Skills

data science / data engineering studies, with python and databases knowledge

Basic knowledge of data analysis tools such as Python, Excel, or any other relevant software. Familiarity with data visualization tools (e.g., Power BI, Spotfire) is a plus.
Strong analytical skills, with an eye for detail. Excellent communication skills and the ability to work collaboratively within a team. Eagerness to learn and adapt to new tools, techniques, and industrial processes.

Diversity and inclusion

ASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that diversity and inclusion is a driving force in the success of our company.

Other information

This internship offers an excellent opportunity to gain practical experience in analyzing machine logs, deriving insights, and contributing to industrialization improvements within our organization. The role emphasizes hands-on learning, data analysis, and collaborative efforts to drive operational enhancements.

EOE AA M/F/Veteran/Disability

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