Student Worker – Turning Bid Archives into a Service Pipeline

Siemens AG; Stockholms kommun; Hybrid; SEK 276,000 - 441,000; Part time

Job summary

Siemens AG in Solna is seeking a hands-on student to build an AI-driven data extraction and analytics pipeline for Smart Infrastructure. You will extract structured data from PDFs, design schemas, and connect results to service records to support the sales and service teams.

Ideal candidates are pursuing CS/engineering/data science with 1–2 years left, comfortable turning vague problems into working demos, and familiar with Python, SQL, and Power BI. Hybrid office setup in Solna awaits.

Qualifications

• Student in CS/engineering/data science with 1–2 years left.
• Interest in turning vague business problems into runnable solutions.
• Hands-on AI/automation experience with agents, chatbots, or workflows.
• Structured, proactive, and self-driven; strong in iterative prototyping.

Responsibilities

• Build extraction pipelines to pull structured data from PDFs.
• Model data schemas for a unified installed-base view.
• Resolve duplicates by matching sites across names and systems.
• Score opportunities and rank service opportunities for sales.
• Deliver Power BI dashboards for the Customer Service team.

Skills

SQL

Python (Pandas)

Data extraction

Power BI

LLMs for extraction

Education

Student in Computer Science/Engineering/Data Science

Tools

PyMuPDF

pdfplumber

OCR

Job description

Job ID

524728

Posted since

13-Oct-2026

Organization

Smart Infrastructure

Field of work

Internal Services

Company

Student (Not Yet Graduated)

Job type

Part-time

Hybrid (Remote/Office)

Employment type

Fixed Term

Location(s)

• Solna - Stockholms laen - Sweden

About the role

Siemens is a global technology leader shaping the future of electrification, automation, and digitalization. Within Smart Infrastructure, we are driving the transformation of digital sales to create modern, data-driven customer experiences.

Are you passionate about practical AI and automation? We are now looking for a hands‑on and curious student to join our Digital Sales team. You will build an extraction pipeline, resolve entity inconsistencies, and connect this data with service records. Your goal is to turn a dusty document archive from our installed base into an actionable service and retrofit pipeline that our Customer Service team will actually use.

This is not a research position - you will be building real solutions used by our sales team. This is a real data engineering, extraction and analysis work.

Your responsibilities

• Build Extraction Pipelines: Extract structured data (customer, site, equipment, configuration, dates) from historical PDFs, handling template drift and scanned documents.
• Model the Data: Design the data schema alongside the team to support a unified view of our installed base.
• Resolve Entities & Clean Data: Tackle messy duplicates—matching customer sites across different names, spellings, and systems.
• Score Opportunities: Build logic to identify equipment approaching end‑of‑life and rank commercial service opportunities.
• Deliver Usable Dashboards: Build practical Power BI dashboards for the Customer Service team.

What you will learn

• How AI and automation are applied in modern B2B digital sales
• Hands‑on experience building real AI agents used in business workflows
• End-to-end sales processes and customer journeys
• Exposure to electrification and automation solutions in the energy domain

Who are you?

• Student in Computer Science, Engineering, Data Science, or similar (1 to 2 years remaining)
• You enjoy taking a vague business problem and turning it into something that runs
• Hands‑on experience developing AI agents, chatbots, or automation workflows (not just theoretical)
• Comfortable in iterating, prototyping, and quickly turning ideas into working demos
• Structured, proactive, and self-driven
• Swedish and English are must, additional language is a plus

Technical skills we are looking for

• Strong SQL skills: Comfortable with complex joins, window functions, and multi‑table queries without a tutorial.
• Python data stack: Solid experience with pandas and PDF extraction tools (PyMuPDF, pdfplumber, or OCR).
• Data mindset: You enjoy cleaning messy data, designing schemas, and ensuring accuracy.
• Experience using LLMs for unstructured document extraction (and knowing where they fail).
• Exposure to entity resolution / fuzzy matching techniques.
• Familiarity with Power BI
• Interest in industrial maintenance, equipment lifecycles, or commercial operations.

What we offer

• A unique opportunity to build real AI solutions in a business context
• High level of ownership and the chance to turn ideas into production concepts
• Flexible working hours to combine work with your studies (approx.. 2 days a week)
• A modern, innovative, and collaborative environment
• Office in Solna
• Strong learning and growth opportunities within Siemens

Be part of a global technology leader that empowers customers to accelerate their digital and sustainable transformation. At Siemens, you will work in an innovative environment where your ideas, curiosity, and ambition are valued from day one.

As part of our recruitment process, background checks are conducted on the final candidate.