Monitor and analyse market developments, customer trends, pricing dynamics, and competitor activities to identify opportunities and risks.
Transform complex datasets into meaningful insights that support commercial and strategic decisions.
Develop dashboards, reports, and performance indicators that provide transparency on business performance.
Create forecasts, scenarios, and predictive analyses that enable proactive decision making.
Integrate internal business data with external market intelligence to build a comprehensive view of the market landscape.
Design and implement automated data collection and processing workflows from a variety of internal and external sources.
Automate reporting, data preparation, and analytical processes to improve efficiency, speed, and reliability.
Leverage AI, machine learning concepts, advanced analytics, and programming capabilities to enhance business intelligence and decision support.
Ensure high standards of data quality, consistency, and transparency across analytical outputs.
Act as a trusted analytical partner to stakeholders across Sales, Marketing, Supply Chain, Strategy, and Commercial Excellence.
Contribute to building a strong data-driven culture by helping stakeholders translate insights into action.
Requirements
A university degree in Business Administration, Economics, Data Science, Statistics, Engineering, Computer Science, or a related field.
Experience gained through professional roles, internships, university projects, or relevant analytical assignments in market intelligence, business intelligence, analytics, or related fields.
Strong analytical and problem-solving skills, with the ability to connect data to business outcomes and recommendations.
Hands-on experience with data visualisation and analytics tools such as Power BI, SQL, and advanced Excel.
Programming skills in Python, R, or a similar language are essential, with the ability to automate workflows, manipulate datasets, and develop analytical solutions.
An interest in AI-powered tools, advanced analytics, and emerging technologies that improve business decision making.
Understanding of data integration, data modelling, and data quality principles.
Strong communication skills and the ability to explain complex findings to both technical and non-technical audiences.
A proactive, curious, and continuous-improvement mindset.
Experience within manufacturing, industrial, packaging, or B2B environments would be an advantage.