Data Scientist

Job Title: Data Scientist
Department: Advanced Analytics - Actuary
Reports: Predictive Analytics Manager
Location: Blanchardstown, Dublin


Job Summary

Provides predictive modelling and advanced analytics services to key functions across the organisation.

As Liberty Ireland (LI) builds its analytical capability this Data Scientist role will leverage the large Data Scientist community in our US business, our team in Belfast, as well as our actuarial team in Dublin to develop their own skills and to deploy best practice approaches to data management and advanced analytics.


Key Tasks & Responsibilities

  • Apply sophisticated, cutting-edge statistical techniques to very large data sets in the course of predictive modelling and various analytical projects. Examples of the techniques include Decision Trees, Clustering, GLM, Text based analytics
  • Build complex tools and analytical models for use by business operations and/or functional groups (e.g. Pricing, Underwriting, Marketing, etc.)
  • Produce meaningful observations and recommendations through synthesizing data from internal and external sources. (E.g. economic, weather, customer surveys, social media activity, etc.)
  • Present findings / recommendations to analytics peers and/or management
  • Carry out predictive modelling and other analyses to solve business problems and enhance strategic goals
  • Perform data preparation steps, including extraction of target data from multiple databases, integration of multiple datasets, and creation of derived variables, application of business rules, and quality control checks
  • Collaborate with other advanced analytics staff to share best practices in predictive modelling and build the advanced analytics community



  • Master's degree in Mathematics, Computing, Statistics or another quantitative field
  • For non-Masters’ Degree candidates, Bachelor's Degree (minimum 2.1) and proven applied business / non-academic experience


Experience & Knowledge

  • Experience / understanding of using statistical techniques e.g. regression analysis, cluster analysis and optimisation.
  • Identification of relevant statistical techniques for addressing various problems.
  • Strong technical background; comfortable with programming and / or use of statistical software packages (Anaconda, R, SAS, Emblem etc.…)
  • Previous use of various analytical methodologies, e.g. Random Forest, Neural Networks, K-means clustering, etc.
  • Knowledge of big data concepts, strategies, and methodologies
  • Previous experience using machine learning and big data products within Amazon Web Service (AWS) is highly desirable
  • Ability to identify and communicate limitations of tools and methods
  • Knowledge of data sources, tools and business drivers
  • Understanding of the insurance industry, including external influences and internal functions is key



  • Able to plan own work to meet deadlines
  • Ability to adapt to evolving techniques and changing business challenges
  • Actively utilise data quality and data preparation best practices (documentation, GIT versioning, etc)
  • Ability to find creative solutions to problems
  • Able to collect, analyse and challenge technical information
  • Distils complex quantitative and qualitative information into key facts and makes well-reasoned recommendations to management
  • Effective communicator with the ability to generate and present insights in a way that can be clearly understood by both technical and non-technical audiences.
  • Ability to clearly link analytical output to the business solution
  • Good interpersonal skills, works closely with other individuals/teams to achieve goals
  • Seeks to maximise the benefits of a team focussed organisation and supports collaboration
  • Highly motivated to deliver consistent high performance


Liberty Insurance is an Equal Opportunity Employer.


If you would like to apply for any of the above positions please submit your CV to

Alternatively, if you require further information on this vacancy, please contact our
Human Resources Department on +353 (0)1 553 4060.