At a Glance
- Tasks: Build scalable data solutions that enhance customer engagement and marketing performance.
- Company: Join LexisNexis® Risk Solutions, a leader in data analytics and risk management.
- Benefits: Enjoy remote work, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment with dynamic teams focused on innovation.
- Why this job: Make a real impact by turning complex data into actionable insights.
- Qualifications: Strong SQL skills and experience with cloud data platforms required.
The predicted salary is between 60000 - 80000 £ per year.
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?
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.
The MarTech – Marketing Automation team is a dynamic group managing several SaaS-based solutions within the Marketing Technology stack for LNRS Data Services. 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.
- 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
- 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
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).
StudySmarter Expert Advice🤫
We think this is how you could land Data Science Data Science Senior Data Scientist (Remote) in City of London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like LexisNexis Risk Solutions!
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Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Science Data Science Senior Data Scientist (Remote) at LexisNexis Risk Solutions.
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like LexisNexis Risk Solutions.
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We think you need these skills to ace Data Science Data Science Senior Data Scientist (Remote) in City of London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at LexisNexis Risk Solutions, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at LexisNexis Risk Solutions. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at LexisNexis Risk Solutions!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
