Data Scientist – Underwriting Analytics

Jobtailor; Dublin; On-site; EUR 70,000 - 110,000; Full time

Job summary

Jobtailor in Dublin is seeking a data scientist to lead development of analytical models for underwriting and pricing. You will design robust data pipelines and datasets to support MI, dashboards and analytics, and own forecasting processes with scalable, well-documented outputs.

The role requires 2–5 years in a quantitative field, strong Python or R skills, and experience with GLMs, tree-based methods, time series forecasting, clustering, and Power BI/Tableau. Dublin-based opportunity.

Qualifications

• Bachelor’s degree in a quantitative discipline.
• 2–5 years in data science, analytics, actuarial, or a related field.
• Strong coding skills in Python or R.
• Experience with GLMs, tree-based methods, time series forecasting, clustering.
• Experience with Power BI or Tableau.

Responsibilities

• Lead development of analytical solutions and models for underwriting and pricing.
• Design, build and maintain data pipelines and datasets for MI, dashboards, analytics.
• Own complex reporting and forecasting processes, ensuring accuracy and scalability.
• Enhance MI for underwriting and performance KPIs with advanced analytics.
• Develop and maintain forecasting models to support planning and portfolio steering.

Skills

Statistical thinking

Data-driven decision making

Education

Bachelor’s degree in quantitative field

Tools

Python

R

Power BI

Tableau

Job description

• Leading the development of analytical solutions and models to support underwriting and pricing decisions.
• Designing, building and maintaining robust data pipelines, datasets and codebases that support regular MI, dashboards and advanced analytics.
• Taking ownership of more complex reporting and forecasting processes, ensuring they are accurate, scalable and well‑documented.
• Enhancing existing MI for Underwriting and Performance KPIs, introducing more advanced analytics.
• Developing and maintaining financial and performance forecasting models to support planning and portfolio steering.

Requirements

• Bachelor’s degree (or equivalent) in Mathematics, Statistics, Actuarial Science, Data Science, Computer Science, Engineering, Economics, Finance or a related quantitative discipline.
• Typically 2–5 years of experience in data science, advanced analytics, actuarial, or a closely related field.
• Strong coding skills in at least one of Python or R.
• Practical experience with statistical modelling and/or machine learning techniques, such as: Generalised linear models (GLMs) or other regression methods, Tree-based methods (e.g. random forests, gradient boosting), Time series modelling and forecasting, Clustering and segmentation technique.
• Experience with data visualisation tools such as Power BI or Tableau.