Principal Data Scientist

About the Company

LexisNexis Risk Solutions is a crucial partner in the evaluation of risk, providing advanced technology and analytics solutions within the insurance sector. Their insurance vertical combines public and industry-specific data to assist customers in risk assessment and operational efficiency enhancement across the insurance policy lifecycle.

Team Overview

The global Data Science team within Insurance consists of over 150 data scientists worldwide, including 25 professionals based in Dublin. This team supports initiatives across Ireland, the UK, and the EU, focusing on maintaining existing products, R&D for new solutions, and promoting data-driven decision making in pricing, underwriting, claims, and fraud detection.

Role Summary

The Principal Data Scientist position acts as a senior technical leader and individual contributor, supporting multiple projects spanning data science, infrastructure, and product innovation. This role involves shaping the product roadmap, building scalable machine learning workflows, and collaborating cross-functionally to deliver impactful solutions aligned with business objectives.

Key Responsibilities

• Investigate Generative AI and machine learning solutions developed by US counterparts and assess applicability locally.
• Explore other AI technologies to enhance current offerings.
• Provide expert data science guidance across various projects and domains.
• Support cloud migration efforts in partnership with technology teams ensuring alignment with organizational goals.
• Handle large datasets (mostly structured, some unstructured), creating workflows to feed products and generate insights.
• Design, test, and document best data science practices in cloud environments to maintain operational excellence.
• Develop and prototype innovative solutions improving accuracy, efficiency, and productivity via available infrastructure.
• Enable large-scale benchmarking and share insights from proprietary data collections.
• Create predictive models for insurance applications such as claim frequency and severity, incorporating embedding layers to enhance performance.
• Build and deploy new data products including ETL pipelines and statistical models collaboratively with technology teams.
• Work closely with technology partners to enhance end-to-end machine learning workflows from data ingestion through deployment and monitoring.
• Collaborate with product, technology, and data engineering stakeholders to align priorities and vision.
• Convey complex analytical results effectively to both technical and non-technical stakeholders.
• Develop solutions utilizing open-source and proprietary tools.
• Present progress updates internally and externally as required.
• Define project requirements, timelines, and execution strategies in cross-functional teams.
• Mentor team members fostering a culture of technical excellence and continuous development.

Candidate Requirements

• A degree in Mathematics, Statistics, Physics, Computer Science, or related quantitative discipline; advanced degree is preferred.
• Eight or more years of professional experience in data science or related areas (time in MSc/PhD programs can count as experience).
• Proficient in programming with Python (preferred) or R, with some exposure to Azure ML Flow, Apache Spark, and distributed computing environments.
• At least three years of industry experience constructing and deploying predictive mathematical models into production.
• Strong expertise in data processing including extraction, cleaning, transformation, and handling various formats (Avro, Parquet, JSON, XML).
• Experience creating robust, maintainable data pipelines and adhering to software engineering best practices.
• Advanced SQL skills and familiarity with both relational and NoSQL databases.
• Ability to interpret, report, and communicate data insights focusing on accuracy, consistency, and business impact.
• Excellent communication skills to engage diverse audiences.
• Experience leading and mentoring technical teams and managing technical workstreams.
• Familiarity with version control (Git), documentation protocols, and collaborative software development.
• Knowledge of MLOps, Azure ML/storage, Azure architecture, Databricks, Linux, business intelligence tools, insurance domain exposure, model governance, explainability, and ethical AI principles.

Additional Information

The primary location is Dublin, Ireland, with a base pay range of €75,300 to €125,600.
LexisNexis Risk Solutions values employee well-being and offers country-specific benefits.
The company is committed to an inclusive and accessible hiring process and equal employment opportunities regardless of race, gender, age, disability, or other protected characteristics.
Candidates with disabilities can request accommodations for the hiring process.
Applicants should beware of fraudulent recruiters and never share financial or personal information.
Women in Data® supports this role, connecting female data professionals within the UK and Ireland.