Hybrid Data Analyst/Scientist — Power BI & ML for Quality

Scania; Stjärna; Hybrid; SEK 750,000 - 950,000; Full time

Benefits offered by this job

Hybrid work

Health center access

Wellness allowance

Result bonus

Flexible hours

Company car leasing

Job summary

Scania is seeking a Data Analyst/Scientist to strengthen the Quality Information team within the Brand Identity Development Field Quality organization. You will provide statistical support and build data models from vehicle production, warranty, fault codes, and operational data using Power BI and SAS Viya.

You will collaborate with analysts and data engineers in Södertälje and Brazil, contribute to cloud-first initiatives with Azure and Snowflake, and apply machine learning to uncover

Qualifications

• Degree in engineering, computer science or similar field with strong analytical skills.
• Proficiency in SQL coding and building reports in Power BI or SAS Viya.
• Experience with Power BI or SAS Viya is a plus.

Responsibilities

• Build and modify Power BI reports, perform advanced analysis, and create data models related to customer vehicles.
• Dive into machine learning to uncover new insights and benefits in our data.
• Collaborate with analysts and data engineers in Södertälje and Brazil to enable data-driven decisions.
• Participate in management meetings for yearly planning and follow-ups.

Skills

Statistical Analysis

DAX Programming

SQL Server & SSAS

Building Reports in Power BI

Python or R Programming

Education

Engineering/CS degree

Tools

Power BI

SAS Viya

Azure

Snowflake

Job description

Scania is seeking a Data Analyst/Scientist to strengthen the Quality Information team within the Brand Identity Development Field Quality organization. You will provide statistical support and build data models from vehicle production, warranty, fault codes, and operational data using Power BI and SAS Viya.

You will collaborate with analysts and data engineers in Södertälje and Brazil, contribute to cloud-first initiatives with Azure and Snowflake, and apply machine learning to uncover