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For Companies At a Glance
- Tasks: Drive data science projects and tackle real-world business challenges with innovative analytics.
- Company: Join LexisNexis Risk Solutions, a leader in risk assessment and analytics.
- Benefits: Enjoy private medical benefits, wellbeing programs, and extensive learning resources.
- Why this job: Make an impact by using data to enhance decision-making across the insurance industry.
- Qualifications: Experience in data science, proficiency in SQL, and knowledge of Python or R required.
- Other info: Collaborative team environment with opportunities for mentoring and career growth.
The predicted salary is between 28800 - 48000 ÂŁ per year.
LexisNexis Risk Solutions is the essential partner for risk assessment. Within our Insurance business, 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 solutions help drive better data‑driven decisions across the insurance lifecycle, all while reducing risk and optimising processes.
About the Team
You will join a collaborative team of technical specialists who support data science initiatives across the UK, Ireland, and Europe. The team works closely with colleagues in Technology, Product, Account Management, Project Management, Marketing, Finance, and Legal to improve products and support data‑informed decision‑making.
About the Role
This role is suited to an experienced data professional who enjoys working across a variety of projects. You will apply data science and analytics techniques to real‑world business challenges, contribute to new and existing products, and communicate insights clearly to a wide range of audiences. We welcome candidates from diverse backgrounds and career paths who meet most—but not necessarily all—of the criteria below.
Responsibilities
- Contribute to data science projects across multiple business areas
- Design and build analytical solutions, including data processing, statistical analysis, and machine learning
- Explore new datasets and identify practical, high‑value use cases
- Work collaboratively with technology, product, and data engineering teams to deliver reliable, production‑ready solutions
- Communicate analytical findings clearly to both technical and non‑technical stakeholders
- Support project planning, including requirements, timelines, and delivery
- Help improve analytics platforms and cloud‑based workflows, including testing and migration activities
- Use a combination of open‑source and proprietary tools to develop solutions
- Share knowledge and support the development of colleagues through mentoring and collaboration
- Travel occasionally between the UK and Ireland for meetings or workshops, where required
Skills and Experience
- Professional experience in data science, analytics, or a related field
- Strong experience working with data, including extracting, cleaning, and transforming structured and semi‑structured data
- Proficiency in SQL and in at least one programming language such as Python or R
- Experience or interest in scalable data processing (e.g. distributed or cloud‑based systems)
- Understanding of data quality, integrity, and maintainable code practices
- Familiarity with version control and collaborative development practices
- Ability to communicate complex ideas clearly in writing and verbally
- Experience working in regulated or commercial environments is helpful but not required
- A degree or equivalent practical experience in a quantitative, technical, or analytical field
- Advanced degrees and formal certifications are valued but not essential
Working for you
We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
- Private medical benefits
- Wellbeing programs
- Life assurance
- Group income protection
- Access to a competitive contributory pension scheme
- Employee Assistance Programme
- RECARES days, giving you time to support the charities and causes that matter to you
- Access to employee resource groups with dedicated time to volunteer
- Access to extensive learning and development resources
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.
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.
Senior Data Scientist employer: Lexis Nexis
Contact Detail:
Lexis Nexis Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current or former employees at LexisNexis Risk Solutions on LinkedIn. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Prepare for the interview by brushing up on your data science skills. Be ready to discuss your experience with SQL, Python, and machine learning techniques. We want to see how you tackle real-world problems!
✨Tip Number 3
Showcase your projects! Bring along examples of your previous work that highlight your analytical skills and problem-solving abilities. We love seeing how you've applied data science in practical scenarios.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows us you’re genuinely interested in joining our team at LexisNexis Risk Solutions.
We think you need these skills to ace Senior Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with data science, analytics, and any relevant projects you've worked on. We want to see how your skills align with our needs!
Showcase Your Skills: Don’t forget to showcase your technical skills, especially in SQL and programming languages like Python or R. We love seeing practical examples of how you've used these skills in real-world scenarios.
Communicate Clearly: When writing your application, communicate your ideas clearly and concisely. Remember, we’re looking for someone who can explain complex concepts to both technical and non-technical audiences, so show us you can do that!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Lexis Nexis
✨Know Your Data Science Stuff
Make sure you brush up on your data science techniques, especially in SQL and programming languages like Python or R. Be ready to discuss how you've applied these skills in real-world scenarios, as this role involves tackling practical business challenges.
✨Showcase Your Collaborative Spirit
Since the team works closely with various departments, highlight your experience in collaborative projects. Share examples of how you've worked with tech, product, or engineering teams to deliver solutions, and emphasise your ability to communicate complex ideas to both technical and non-technical audiences.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities. Think about specific projects where you identified high-value use cases or improved processes. Be ready to explain your thought process and the impact of your contributions on the overall project.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the team’s current projects, the tools they use, or how they measure success. This shows your genuine interest in the role and helps you gauge if it’s the right fit for you.