ArcelorMittal South Africa | View - Senior Specialist, Data Scientist

Senior Specialist, Data Scientist - Business Analytics, Vanderbijlpark (S3)

Listing reference: arcmt_000935

Listing status: Online

Apply by: 25 September 2026

Position summary

Industry: Steel Industry

Job category: IT and Telecommunications

Location: Vanderbijlpark

Contract: Permanent

Remuneration: Market Related

EE position: No

About our company

Part of the worldwide ArcelorMittal group with an industrial presence in 27 countries, ArcelorMittal South Africa Limited is the largest steel producer on the African continent, with a production capacity of 5 million tonnes of liquid steel per annum. Both flat and long steel is produced in hundreds of grades and specifications. Steel is as relevant as ever to the future success of our world. As one of the only materials to be completely reusable and recyclable, it will play a critical role in building the circular economy of the future. Steel will continue to evolve, becoming smarter, and increasingly sustainable. At ArcelorMittal, our goal is to help build a better world with smarter steels.At ArcelorMittal South Africa, our "We Care" value drives our unwavering commitment to safety and zero harm for our employees. We seek applicants who share this dedication and are ready to uphold our high safety standards.It is essential to regularly check your emails for updates regarding your application status. We utilise "Wamly”, a one-way recorded interview platform, to streamline our hiring process. Should you receive an invitation to complete a recorded interview, please ensure it is submitted by the specified deadline. Timely completion of this step is crucial for your application to be considered for the opportunity. We appreciate your diligence in this process and look forward to your participation.

Introduction

ArcelorMittal is recruiting for a Senior Specialist, Data Scientist - Business Analytics, Vanderbijlpark (S3)

Job description

Responsibilities & requirements

· Design and develop scalable enterprise reporting and analytics solutions.

· Build and maintain Azure Data Factory and Synapse pipelines.

· Develop high-performance Power BI semantic models and dashboards.

· Translate business requirements into data products and actionable insights.

· Develop AI and machine learning solutions to improve operational performance.

· Implement data quality, governance and automation best practices.

· Support business stakeholders with analytical recommendations and decision support.

· Drive innovation through modern data, analytics and AI technologies.

Minimum requirements

Qualifications & requirements

· B Degree (NQF 7/10) or M-Dip (NQF 7/8 or NQF 8/10) in Engineering, Data Science, Computer Science, or related field.

· Machine Learning or Business Intelligence related certifications will be advantageous.

· A postgraduate qualification would be an advantage

· 8 Years experience in IT

· 3–5 years experience in data engineering, analytics, reporting or business intelligence.

· Strong experience with Power BI, data modelling, DAX and performance optimisation.

· Hands-on experience with Azure Data Factory, Azure Synapse Analytics, PySpark and SQL.

· Experience integrating SAP, Oracle, SQL Server and cloud-based data platforms.

· Some exposure to Azure OpenAI, Cognitive Search, machine learning and AI-enabled solutions.

· Experience with Logic Apps and Power Automate.

· This position is a development position for a data scientist. Some knowledge of python and an interest in data science will be advantageous in the future. Willing to learn and start experimental projects in this regard is a key requirement. This will include the building of some Agentic AI applications and Classical Machine learning projects after some training and development.

Personal Attributes

· Strong analytical thinking and problem-solving capabilities.

· Ability to apply data science to real-world manufacturing challenges.

· Effective communicator with the ability to explain technical concepts to non-technical stakeholders.

· Collaborative and capable of working in cross-functional teams.

· Results-oriented with a strong sense of accountability and initiative.

· High attention to detail and strong organizational skills.

· Adaptable, self-driven, and committed to continuous learning.

· Ability to work independently and manage multiple priorities