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Overview

KONE Oyj company logo
Summer Trainee, Machine Learning - KONE Oyj - Espoo, Finland
Data Scientist
Compensation
6,000 - 8,000/month
Salary Context: Data Scientist
Market Average: Data Scientist
€2,250 - €19,894
In Espoo, Finland: Data Scientist
€6,000 - €8,000
This Offer
€6,000 - €8,000
€2,250€19,894
per month
Location
Espoo
Remoteness
Hybrid
Estimated Expiry
February 18, 2026
Management Tier
No People Management
Job Type
Full-time
Posted: January 14, 2026
Required:
English

Job Description

A summer traineeship at KONE R&D focusing on machine learning pipelines, data analysis, visualization, and predictive modeling in a cloud environment, aimed at students in final university stages.

Apply on Company Website

Company Information

KONE Oyj company logo

KONE Oyj

Manufacture of lifting and handling equipment
Kartanontie 1 00330 HELSINKI
Business ID: 1927400-1
Headcount: 1,254
Company Age: 21 years
About

KONE Oyj on julkinen osakeyhtiö, jonka toimiala on nosto- ja siirtolaitteiden valmistus ja kotipaikka Espoo. Vuonna 2024 KONE Oyj työllisti 1254 henkilöä ja sen liikevaihto oli 794,5 milj. euroa, kasvaen 12% vuoteen 2023 verrattuna. Työnantajalla on tällä hetkellä 5 avointa työpaikkaa Duunitorilla, katso kaikki avoimet työpaikat täältä.

Financial Overview (2024)

KONE Oyj was profitable in 2024 with revenue of €794.5M and a profit margin of 0.3%.

€794.5MRevenue€229.2MProfit0.3%Profit Margin

Data shown is based on historical job postings from our database.

Job Details

Requirements

  • Studies in data science, machine learning, data engineering, software engineering, computer science, physics, statistics, mathematics
  • Experience in SQL and database understanding
  • Interest in programming in Python
  • Knowledge of data science tools (e.g., sklearn, Pandas, Spark)
  • Experience with big data tools, neural networks, cloud services (plus)
  • Understanding of SW engineering principles (advantage)
  • Good analytical skills
  • English communication skills

Responsibilities

  • Work on data and machine learning pipelines
  • Perform data analysis and visualization
  • Develop dashboards and monitor data quality
  • Resolve incidents and bugs
  • Gain understanding of devops, dataops, mlops practices

Field:

Data

Education Level

Masters

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