Data Scientist Data Scientist

Ornua’s core purpose is to build profitable routes to market for Irish dairy products.

The Group is structured across two divisions: Ornua Foods and Ornua Ingredients. Ornua Foods is responsible for the marketing and sales of Ornua’s consumer brands, including Ireland’s most successful food export, Kerrygold, as well as Kerrygold Dubliner, Pilgrims Choice, Forto and BEO milk powders.

Ornua Ingredients is responsible for the procurement of Irish and non-Irish dairy products, for the sale of dairy ingredients to food manufacturing and foodservice customers across the world, and for managing volatility through de-risking and trading strategies.

Ornua’s Values

At Ornua, our Values lie at the core of everything that we do and how we behave both individually and as a business. Our five values, and their underlying behaviours, encourage us to Seek and Embrace New Ideas, Make It Happen, Be Our True Selves, Show You Care and Achieve Great Things Together.

Ornua’s Growth

At Ornua, our co-operative ethos lies at the heart of how we do business. We care passionately about driving sustainable, profitable growth, underpinned by our ambitious ‘Path to Prosper’ strategy. We have delivered significant growth in our core business, and we have ambitious plans for continued growth over the next five years.

WHY THIS ROLE IS VALUABLE

By providing actionable insights, we empower better decision-making, enhance productivity, and drive scalable growth across the entire organization.

The Data Scientist plays a key role in guiding stakeholders through the journey of building a data-driven organization.

KEY AREAS OF RESPONSIBILITY:

• 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.
• Innovation: Drive the adoption of new approaches and technologies, such as artificial intelligence (AI), to enhance data analytics capabilities and deliver cutting-edge solutions.

KEY REQUIREMENTS:

• Excellent technical skills including proficiency in programming languages such as Python or R, and experience with data analysis and visualization tools (e.g., SQL, Power BI, Tableau).
• Strong background in statistics, data analysis, and machine learning techniques.
• Ability to understand business processes and translate business needs into data-driven solutions.
• Excellent communication skills with proven ability to convey complex technical concepts to non-technical stakeholders and build strong relationships with business partners.
• Strong analytical and problem-solving skills to identify and address data-related challenges.
• Prior experience in data science or related fields, with a track record of building successful data products.
• 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.
• Experience in the foods sector and developing use cases such as global supply chain, trading, pricing, and logistics is an advantage.
• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field. Relevant certifications in data science or analytics (e.g., Certified Data Scientist, Microsoft Certified: Data Scientist Associate) are a plus.

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