Job Description

Job Title: Data Scientist

Career Level: P3

Function: Technology

Reports to: Head of data and analytics

Location: Dublin

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Ornua is a leading dairy co-operative which sells premium dairy products globally on behalf of its Member Co-operatives, Ireland’s dairy processors and, in turn, Irish dairy farmers.

Ornua has revenues of €3.4 billion and is supported by a global team of approximately 2,800 employees. The Group operates as a commercial organisation across 10 business units, including 12 production facilities located in Europe, North America, the Middle East and Africa.

The commercial organisation is responsible for the marketing and sales of Ornua’s consumer brands including Ireland’s most successful food export: Kerrygold. Consumer markets are served by production facilities in Ireland, Germany and the UK and by in-market Sales & Marketing Teams in Asia, Germany, Ireland, MEA, Poland, Spain, rest of Europe and North and Latin America.

It also manages the procurement of Irish and non-Irish dairy products, the sale of dairy ingredients to food manufacturing and foodservice customers globally, and the implementation of de-risking and trading strategies to manage market volatility. These activities are supported by production facilities and in-market teams in Europe, North America, the Middle East and Africa.

WHY THIS ROLE IS VALUABLE:

The newly established Data & Analytics team is a pivotal group-wide function dedicated to revolutionizing our approach to data. Our mission is to deliver transformative data and analytics solutions that unlock the full potential of our data assets. By providing actionable insights, we empower better decision-making, enhance productivity, and drive scalable growth across the entire organization.

KEY AREAS OF RESPONSIBILITY:

Responsible for leveraging data to build innovative data products that drive business value. This role involves partnering with business stakeholders to develop data products that range from basic descriptive and diagnostic analytics to advanced predictive and prescriptive analytics. The Data Scientist plays a key role in guiding stakeholders through the journey of building a data-driven organization.

Key Responsibilities:

• Data Product Development: Design, build, and maintain data products that provide valuable insights and support business objectives.
• Stakeholder Collaboration: Partner with business stakeholders to understand their needs and translate them into data-driven solutions.
• Descriptive and Diagnostic Analytics: Develop and implement descriptive and diagnostic analytics to understand past and current business performance.
• Predictive and Prescriptive Analytics: Create predictive models and prescriptive analytics to forecast future trends and recommend actions.
• Data Visualization: Develop compelling data visualizations and dashboards to communicate insights effectively to stakeholders.
• Data Quality and Governance: Ensure data quality, consistency, and governance across all data products.
• Continuous Improvement: Continuously improve data products and analytics processes based on stakeholder feedback and evolving business needs.
• Education and Advocacy: Educate stakeholders on the value of data-driven decision-making and advocate for a data-driven culture within the organization.
• Technology Architecture Roadmap: Develop the technology architecture roadmap for Data Science to ensure scalable, efficient, and future-proof data solutions.
• InnovationDrive the adoption of new approaches and technologies, such as artificial intelligence (AI), to enhance data analytics capabilities and deliver cutting-edge solutions.

KEY REQUIREMENTS:

• Experience: 3 years’ experience
• Technical Skills: Proficiency in programming languages such as Python or R, and experience with data analysis and visualization tools (e.g., SQL, Power BI, Tableau).
• Statistical and Analytical Skills: Strong background in statistics, data analysis, and machine learning techniques.
• Business Acumen: Ability to understand business processes and translate business needs into data-driven solutions.
• Communication Skills: Excellent communication skills to convey complex technical concepts to non-technical stakeholders and build strong relationships with business partners.
• Problem-Solving: Strong analytical and problem-solving skills to identify and address data-related challenges.
• Experience: Prior experience in data science or related fields, with a track record of building successful data products.
• MLOps: Knowledge of MLOps practices, including the deployment, monitoring, and maintenance of machine learning models in production. Familiarity with tools and frameworks such as Docker, Kubernetes, MLFlow, and Kubeflow.
• Industry Experience: Experience in the foods sector and developing use cases such as global supply chain, trading, pricing, and logistics is an advantage.

Education and Training:

• Degree: Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
• Certifications: Relevant certifications in data science or analytics (e.g., Certified Data Scientist, Microsoft Certified: Data Scientist Associate) are a plus.

Closing Date: 30 July 2026