Senior Data Scientist II
At a glance
Senior Data Science role at LexisNexis® Risk Solutions. London Wall · full-time · no salary stated · we estimate £81,900–£111,875 across the United Kingdom.
LexisNexis® Risk Solutions has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Build data pipelines that bring customer, campaign and operational information into the CDP and marketing data layer
- Shape data models for audience segmentation, lifecycle analysis, attribution and KPI tracking
- Improve data accuracy through validation, deduplication and optimisation for analytics and reporting
- Prepare identity, consent and audience data, then create event triggers for real-time customer journeys
- Set up governance controls and structured datasets for dashboards, analytics and compliant data use
What you bring
- Strong SQL skills and hands-on work with ETL or ELT processes and pipeline orchestration tools
- Experience using cloud data platforms such as Azure, AWS or GCP
- You can model data and understand marketing systems, including CDPs, CRM and behavioural data
- You understand data quality, governance and secure handling, including GDPR and PII requirements
- You can turn business needs into technical solutions and work with both technical and non-technical partners
Who this fits
This role suits a senior data scientist focused on marketing data infrastructure, customer engagement and analytics. The position is based in London Wall, United Kingdom.
From the employer
Are you motivated to build scalable data solutions that directly shape customer engagement and marketing performance?
Do you enjoy collaborating across teams to turn complex data into actionable insights and real-time decision making?
About the Business
LexisNexis® Risk Solutions provides customers with solutions and decision tools that combine public and industry-specific content with advanced technology and analytics to assist in evaluating and predicting risk and enhancing operational efficiency.
We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we help make communities safer, insurance rates more accurate, commerce more transparent, business decisions easier, and processes more efficient.
About Our Team
The MarTech – Marketing Automation team is a dynamic group managing several SaaS-based solutions within the Marketing Technology stack for LNRS Data Services.
About the Role
This role focuses on building and optimising data infrastructure that enables advanced marketing and customer data capabilities. You will create scalable pipelines, data models, and governance practices that support analytics, segmentation, and real-time engagement. Working closely with cross-functional teams, you will help deliver reliable, high-quality data solutions that drive business outcomes.
Responsibilities
- Build and maintain scalable data pipelines integrating customer, campaign, and operational data into the CDP and marketing data layer
- Design and manage data models to support segmentation, lifecycle analytics, attribution, and KPI measurement
- Ensure data quality, consistency, deduplication, and optimisation for analytics and reporting use cases
- Enable CDP functionality including identity resolution, consent management, and audience readiness
- Develop event streams and triggers to support customer journey orchestration and real-time decisioning
- Provide structured datasets and semantic layers for dashboards and advanced analytics
- Implement data governance practices, including lineage, cataloguing, validation, and GDPR/PII compliance
- Partner with analytics, MarTech, and marketing teams to align data solutions with business needs
Requirements
- Strong SQL skills and experience with ETL/ELT and pipeline orchestration tools (e.g., Airflow, dbt, Data Factory)
- Experience with cloud data platforms (e.g., Azure, AWS, or GCP)
- Proficiency in data modelling (dimensional, entity-relationship, event-driven)
- Understanding of marketing data ecosystems, including CDPs, CRM, and behavioural data
- Experience supporting analytics and BI tools (e.g., Power BI, Tableau) from a data engineering perspective
- Knowledge of data governance, quality frameworks, and secure data handling (including GDPR/PII)
- Ability to translate business requirements into scalable technical solutions
- Strong collaboration and communication skills with technical and non-technical stakeholders





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