Data Scientist

Introduction

This position is located at the Head Office in Woodmead with a hybrid working arrangement. The Data Scientist will support 13 operational sites throughout the EMEA region by analyzing, processing, modeling, and interpreting data to provide actionable insights. This role functions within a dynamic, startup-like environment inside a larger corporate framework, emphasizing innovation and creative solution implementation.

Responsibilities

• Partner with stakeholders to identify business challenges and data-driven opportunities.
• Gather, clean, and manipulate extensive datasets to extract critical insights and develop predictive models.
• Utilize advanced statistical and machine learning methods to build and deploy accurate predictive and recommendation models.
• Present findings clearly to both technical and non-technical audiences via reports, visualizations, and presentations.
• Work alongside data scientists, engineers, and business analysts to create scalable, efficient data pipelines and workflows.
• Collaborate closely with various sites to understand processes, data collection, and extraction methodologies.
• Continuously assess and refine models and algorithms to maintain their precision and effectiveness.
• Keep abreast of emerging data science and machine learning tools and techniques; suggest innovative tools and strategies to address business problems.
• Manage analytical projects through all phases: initiation, planning, execution, monitoring, control, and closure.
• Perform literature reviews relevant to ongoing work.
• Maintain client relationships and manage expectations by regular communication.
• Develop Power BI dashboards and manage data integration.

Qualifications and Requirements

• A Bachelor’s degree in Industrial Engineering, Chemical/Process Engineering, Computer Science, Electrical Engineering, Metallurgical Engineering, or a similar discipline is required.
• A postgraduate qualification in data science or related field is advantageous.
• Over 3 years of data science experience.
• Deep knowledge of fundamental machine learning algorithms.
• Proficient in programming languages such as Python or R, along with SQL.
• Experience applying machine learning within industrial settings.
• Understanding of deploying machine learning models in production environments.
• Familiarity with databases and data warehousing concepts.
• Skilled in data analysis, including data manipulation, cleansing, and wrangling.
• Strong communication and interpersonal abilities.
• Experienced in report creation and client presentations using MS Office tools (Word, Excel, PowerPoint) and MS Projects.
• Physically fit to pass medical exams required for mining site entry.
• Fluent in English (reading, writing, and speaking).
• Experience in industrial mineral processing is a plus.