Data Scientist

Outokumpu Chrome Oy; Helsinki; On-site; EUR 65,000 - 90,000; Full time

Job summary

Outokumpu Chrome Oy in Helsinki is seeking a skilled Data Scientist to join the Data Science team within the Enterprise Intelligence Platforms, IT department. You will develop and implement AI/ML models to optimize stainless steel and ferrochrome production, improve product quality, and streamline raw material procurement.

You will collaborate with R&D and engineering teams at production sites, communicating analyses to stakeholders with diverse backgrounds.

Qualifications

• Master’s or Bachelor’s degree in a relevant field; Doctoral degree is an advantage.
• At least two years of practical experience in data-science domain.
• Experience with AI/ML, optimization, statistics or computer vision is beneficial.
• Knowledge of Python, R or similar programming languages is mandatory.
• Experience deploying AI/ML models in production is an advantage; Databricks and Azure are used.

Responsibilities

• Develop AI/ML models for production optimization, quality, energy use and raw material optimization.
• Create time series and computer vision algorithms for production processes.
• Productize ML/AI models by integrating them into applications or interfaces.
• Communicate data analysis results to stakeholders and participate in planning (epics, features, user stories).
• Participate in planning, adhere to architectural and cybersecurity standards.

Skills

AI/ML basics

Statistical thinking

Stakeholder communication

Team collaboration

Education

Master’s or Bachelor’s degree

Doctoral degree (advantage)

Tools

Python

R

Databricks

Azure

Version control

Job description

Select how often (in days) to receive an alert for your keyword search:

Helsinki, FI Vilnius, LT Katowice, PL Tornio, FI

We are seeking a skilled Data Scientist to join our Data Science team within the Enterprise Intelligence Platforms, IT department. This role focuses on developing and implementing advanced AI and machine learning models to enhance our stainless steel and ferrochrome production processes. The successful candidate will work closely with various stakeholders to optimize production, improve product quality, and streamline raw material procurement.

We work in close collaboration with development and R&D engineers at our stainless steel and ferrochrome production sites. Part of the job is to communicate data analysis and modelling results to stakeholders with various backgrounds. Also knowledge from manufacturing industries helps in this position. For example, familiarity with such concepts as statistical process control (SPC), six sigma or quality assurance in manufacturing industries is beneficial.

We have also projects with other business units, for example with sales, so expertise e.g. in market forecasting, pricing optimization, document extraction and similar use cases is a benefit.

Key Responsibilities:

• Develop AI and machine learning models for production optimization, end product quality, energy use and raw material optimization.
• Create time series and computer vision algorithms for stainless steel and ferrochrome production.
• Productize ML/AI models by integrating them into other applications or standalone user interfaces.
• Communicate effectively with stakeholders and participate in project planning, including planning of epics, features, and user stories.

Responsibilities:

• Participate in application, PI, and sprint planning.
• Adhere to best architectural and cybersecurity standards.

Requirements:

• Master’s or Bachelor’s degree in a relevant field. Doctoral degree is an advantage.
• At least two years practical experience in data-science domain.
• At least one of the following: expertise in AI/LLMs (incl. deep learning), machine learning, optimization, statistics or computer vision.
• Knowledge of Python, R or similar programming languages is mandatory.
• Enthusiasm using AI coding tools. Experience in extensive use of AI tools in modelling and software development is an advantage.
• Working knowledge of basic developer tools (e.g. version control) and software development principles is required.
• Experience in deploying and managing AI/ML models in production is an advantage. We use mainly Databricks and Azure to host our models and applications.

You don’t need to master all tools and skills mentioned above, but working experience with programming languages is mandatory.

Stakeholders

Collaborate with other EIP teams, R&D engineers, QA engineers, and development engineers from Steel Melting shop, Hot Rolling Mill, and Cold Rolling Mill departments in Tornio.

For more information, please contact Head of Data Science, Mikko Havimo, mikko.havimo(at)outokumpu.com or TA partner Miikka Enbuske, miikka.enbuske(at)outokumpu.com

The selected candidate will be required to pass a security clearance vetting and health check (including drug tests) before commencing employment