Data Scientist

IT Search; Dublin; On-site; EUR 92,000 - 148,000; Part time

Job summary

Leading AI & Data Software House in Dublin is seeking a Data Scientist / Developer to join a high-performing data science team. You will transform large multi-industry datasets into AI products, leveraging foundational ML models and LLM/RAG solutions.

The role emphasizes production-ready code, DevOps practices, and collaboration across data eng, visualization, and product teams, with end-to-end delivery from requirements to deployment.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Analytics, Applied Mathematics, Statistics, or a related quantitative field.
• Deep mathematical and statistical understanding of ML algorithms and models.
• Experience deploying models to production with DevOps workflows (CI/CD, version control, testing).

Responsibilities

• Collaborate with data engineering, visualisation and product teams to design, test and build core algorithms.
• Implement robust, scalable code and data pipelines with CI/CD and testing.
• Contribute to Gen AI, LLM and RAG focused product development and deployment.
• Share ideas and contribute to strategic ML/AI initiatives across business units.
• Manage end-to-end data science lifecycle from requirements to deployment and presentation.

Skills

Python

ML algorithms

DevOps

Data modelling

Big data

Education

Bachelor’s or Master’s degree in CS/Math/Stats

Tools

Azure DevOps

PySpark

Databricks

Tableau

Git

Job description

Contract Type: Daily Rate Contract

Initial Duration: 6 Months (High likelihood of extension)

Client: Leading AI & Data Software House

About the Role

We are seeking a talented Data Scientist / Developer to join a high-performing Data Science team working within a leading AI software house in Dublin. In this role, you will help transform massive multi-industry datasets into high-impact, actionable AI products, leveraging everything from foundational ML models to LLM/RAG solutions.

Key Responsibilities

• Algorithm & Product Development: Collaborate with cross-functional teams (data engineering, visualisation, and product) to design, test, and build core algorithms for new and existing commercial products.
• Productionisation & DevOps: Implement robust, scalable code and pipelines following strict DevOps practices (Git, CI/CD, automated testing, version control).
• Gen AI & LLM Focus: Actively contribute to developing and productionising products focused on Large Language Model (LLM) technologies, modern Gen AI architectures, and RAG systems.
• Strategic Ideation: Share ideas, pitch new concepts, and contribute to the strategic vision for ML and AI application across various business verticals.
• End-to-End Delivery: Manage the full data science lifecycle—from requirements gathering and parameter engineering through to deployment and technical presentation.

Key Requirements & Expertise

• Core Tech Stack: Expert-level proficiency in the Python data stack (pandas, numpy, scikit-learn, scipy).
• ML & Statistics: Deep mathematical and statistical understanding of machine learning algorithms (clustering, regression, neural networks, decision trees, time series, ensemble methods, etc.).
• Productionisation & DevOps: Demonstrated software development experience putting models into production, including DevOps workflows (CI/CD, version control, automated testing—ideally Azure DevOps).
• Data Modelling & Big Data: Solid foundation in data modelling and working with massive, complex datasets.
• Agile & Collaborative: Experience working in cross-functional, fast-paced, customer-focused environments.
• Education: Bachelor’s or Master’s degree in Computer Science, Data Analytics, Applied Mathematics, Statistics, or a related quantitative field.

Desirable / Advantageous:

• Gen LLMs: Hands-on experience developing LLM solutions, RAG architectures, chunking strategies, and deploying Gen AI platforms.
• Cloud & Big Data Tools: Experience with Azure, Azure DevOps, PySpark, Databricks, or Model Lifecycle Management frameworks.
• Data Visualisation: Proficiency with Tableau or similar analytics/visualisation suites.