Data Scientist

• Location: Dublin, Ireland, primarily remote with occasional in-person collaboration
• Team: Product
• Reporting to: Head of Product, US-based
• **Must have Irish/EU Citizenship **

Cpl are partnering with an innovative international technology organisation to recruit a Data Scientist for its growing Product team in Ireland.

This is a hands-on position for a Data Scientist who enjoys solving complex, loosely defined problems and taking ownership from initial investigation through to production delivery. The successful candidate will work across statistical modelling, machine learning, data engineering and analytical problem-solving.

You will contribute to the development of predictive models, classification solutions and scalable data pipelines. The role offers the opportunity to work closely with product, engineering and customer-facing teams while helping turn large and complex datasets into practical insights and reliable technical solutions.

Key responsibilities

• Investigate open-ended data problems, define an appropriate approach and independently develop solutions through testing and iteration.
• Design, develop and maintain machine learning models and production-grade data pipelines.
• Prepare, clean and structure large, complex and sometimes unstructured datasets for analysis and modelling.
• Develop and improve predictive, classification and entity-resolution models.
• Measure model performance against real-world outcomes and refine solutions using data-led feedback.
• Determine when traditional machine learning, automated data integration or LLM-based techniques are most appropriate.
• Work with product, engineering and business stakeholders to translate commercial or methodological questions into clear technical solutions.
• Provide understandable explanations of areas such as model performance, bias, data confidence and coverage limitations.
• Use Python, machine learning libraries, databases and querying tools across the full development lifecycle.
• Explore new technologies and AI-assisted workflows that can improve delivery speed and quality.
• Maintain clear documentation covering methodologies, code, models and data structures.

Experience and skills

• Approximately three to five years of experience in applied data science, machine learning or a closely related technical role.
• Strong Python development skills, with experience using libraries such as pandas, NumPy, scikit-learn, TensorFlow or PyTorch.
• Good understanding of database design, data schemas, efficient querying and reliable pipeline development.
• Practical experience deploying machine learning models into production and monitoring their ongoing performance.
• Ability to work across data preparation, modelling, engineering and production implementation.
• Strong written and verbal communication skills, including the ability to explain technical decisions and trade-offs to non-technical audiences.
• Demonstrated ability to manage work independently, maintain momentum and follow tasks through to completion.
• Degree in Computer Science, Statistics, Applied Mathematics or another relevant discipline. Equivalent practical experience will also be considered.
• Experience with REST API development, Django REST Framework or a comparable framework would be advantageous.

The person

The ideal candidate will be comfortable working in an environment where every problem does not arrive with a predefined solution. You will be proactive, commercially aware and confident making informed technical decisions.

You should enjoy delivering an effective first version, evaluating it against real data and improving it through iteration. Curiosity around emerging tools, machine learning techniques and AI-enabled development approaches will be particularly valuable.

What the role offers

• A high-ownership position within a growing product and data function.
• The opportunity to work across machine learning, data science and data engineering.
• Exposure to complex datasets and meaningful production use cases.
• Collaboration with international product, engineering and business stakeholders.
• A primarily remote working arrangement, with occasional in-person sessions in Dublin.
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