Are you excited by solving complex data challenges, collaborating across teams, and turning ideas into production-ready products?
About the Business
LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle, all while reducing risk. You can learn more about LexisNexis Risk at https://risk.lexisnexis.com/insurance.
About the Role
As part of our team, you will work as a data science expert across a range of projects, helping to design, build, and deliver scalable analytical products. This role offers the opportunity to combine data engineering, statistical analysis, and machine learning to solve complex insurance challenges, while working closely with technology, product, and data engineering teams.
Responsibilities
- Design and develop new products covering data processing, statistical analysis, and machine learning
- Explore and evaluate new datasets, identify high-value use cases, and apply appropriate analytical and machine learning techniques
- Build scalable, production-ready solutions in partnership with technology, product, and data engineering teams
- Communicate complex analytical outcomes clearly to technical and non-technical audiences to demonstrate product value
- Provide regular internal status updates and present project work externally where required
- Contribute to project planning, including requirements definition, timelines, and execution plans
- Support the development of analytics infrastructure, including testing processes and cloud best practices to enable smooth migration
- Mentor and oversee team members in the delivery of project work
- Travel occasionally between the UK and Ireland for meetings or workshops, where required
Requirements
- Strong experience delivering data science, analytics, or machine learning solutions in a professional environment
- You may have a degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science) or equivalent practical experience delivering data science solutions in industry.”
- Strong data processing expertise, including extraction, cleaning, parsing, and working with formats such as Avro, Parquet, JSON, XML, and relational databases
- Strong SQL skills and Python or R
- Experience building data pipelines with automated testing and writing clean, maintainable, and well-tested code
- Strong understanding of data integrity, consistency, and quality
- Excellent collaboration, mentoring, written, and verbal communication skills, including the ability to explain complex topics clearly
- Familiarity with coding best practices, documentation standards, Git-based version control, and Linux environments
- Experience with insurance data or modelling, Azure ML and Azure data storage services, Databricks, Apache Spark, distributed computing, and BI or visualisation tools such as Power BI or R Shiny is welcomed
Risk benefit statement
Learn more about the LexisNexis Risk team and how we work here
Primary Location Base Pay Range: Ireland - Dublin (Rockfield Central) €68,400 - €114,000.We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-855-833-5120.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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Skills Required
- Strong experience delivering data science, analytics, or machine learning solutions in a professional environment
- Degree in a quantitative field (Mathematics, Statistics, Computer Science) or equivalent practical industry experience
- Strong data processing expertise including extraction, cleaning, parsing, and working with Avro, Parquet, JSON, XML, and relational databases
- Strong SQL skills and Python or R
- Experience building data pipelines with automated testing and writing clean, maintainable, well-tested code
- Strong understanding of data integrity, consistency, and quality
- Excellent collaboration, mentoring, written, and verbal communication skills
- Familiarity with coding best practices, documentation standards, Git-based version control, and Linux environments
- Experience with insurance data or modelling, Azure ML and Azure data storage services, Databricks, Apache Spark, distributed computing, and BI/visualisation tools such as Power BI or R Shiny
RELX Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.
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Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
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Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
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Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.
RELX Insights
What We Do
RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.
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