Data Analytics & Digitalization Intern — AI & Dashboards

Bosch Group

Osmangazi

On-site

TRY 67,000 - 112,000

Part time

3 days ago
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Job summary

Bosch Group offers a Smart Start Data Analytics & Digitalization Engineer internship for students in Industrial/Information/Computer Engineering and related fields. You will support data analysis, build dashboards, and contribute to digitalization efforts using Python and SQL.

Strong English skills and teamwork are essential for cross-functional collaboration. The role focuses on data-driven decision making across logistics, planning, and repair processes, with exposure to AI and machine

Qualifications

  • Strong interest in data analytics, AI, ML, and digitalization.
  • Very good command of English.
  • Excellent communication and teamwork skills.

Responsibilities

  • Support data analysis and reporting across material management, planning, logistics, and repair processes.
  • Collect, process, and analyze data to support data-driven decisions and process improvements.
  • Create reports and interactive dashboards using Power BI or Tableau to monitor KPIs and operational performance.
  • Contribute to data modeling and workflow automation using Python and other digital tools.
  • Take part in AI and machine learning projects, including predictive analytics and anomaly detection.
  • Collaborate with cross-functional teams to identify improvement opportunities and implement data-driven solutions.

Skills

Data analytics
AI/ML interest
English communication

Education

Undergrad/Graduate in Industrial Eng / IS / CS

Tools

Power BI
Tableau
Python
SQL

Job description

Bosch Group offers a Smart Start Data Analytics & Digitalization Engineer internship for students in Industrial/Information/Computer Engineering and related fields. You will support data analysis, build dashboards, and contribute to digitalization efforts using Python and SQL.

Strong English skills and teamwork are essential for cross-functional collaboration. The role focuses on data-driven decision making across logistics, planning, and repair processes, with exposure to AI and machine

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