At a Glance
- Tasks: Transform complex data into insights that drive better decisions in the insurance industry.
- Company: Join LexisNexis Risk Solutions, a leader in innovative data solutions.
- Benefits: Enjoy competitive salary, well-being support, and career development opportunities.
- Other info: Collaborative team environment with opportunities for growth and innovation.
- Why this job: Make a real impact by improving data quality and driving efficiency with modern tools.
- Qualifications: 3+ years in data management, strong analytical skills, and advanced SQL knowledge.
The predicted salary is between 40000 - 50000 £ per year.
Are you passionate about transforming complex data into meaningful insights that drive better decisions? Would you like to work with innovative data solutions that help shape the future of insurance risk?
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.
The Data Engineering Team in the UK&I features 20 individuals but sits within a global Data Engineering team of over 400+ individuals. Data Management is currently a team of 2.5 team members but is expanding as our product offerings grow within the UK.
In this role, you will analyse and interpret complex data to support business decisions and improve data quality across the insurance lifecycle. You’ll collaborate with a variety of stakeholders to deliver insights, resolve issues, and contribute to continuous improvement initiatives. This is an opportunity to combine analytical expertise with modern tools to drive efficiency and innovation.
Responsibilities
- Analyse data to support business decisions and clearly communicate findings
- Collaborate with customers, data providers, and internal stakeholders to gather requirements and resolve issues
- Perform data validation, profiling, reconciliation, and quality assessments
- Investigate and resolve data issues using root-cause analysis and track remediation actions
- Develop and modify queries (e.g., SQL) to support research and data quality checks
- Present insights to both technical and non-technical audiences
- Support data onboarding, workflow improvements, and operational efficiency initiatives (including automation/AI use)
- Identify process inefficiencies and contribute to optimisation, risk management, and change initiatives
Requirements
- 3+ years’ experience in data management, analysis, or customer-facing data roles
- Strong analytical skills with experience handling large or complex datasets
- Advanced SQL and Power BI reporting capabilities
- Knowledge of data lifecycle processes (profiling, validation, reconciliation)
- Experience with root-cause analysis and data quality improvement
- Strong communication and stakeholder engagement skills
- Exposure to APIs, data integration formats, and modern data platforms (e.g., Azure) preferred
- Experience using AI/automation tools to enhance analysis and efficiency, with a proactive and detail-oriented mindset
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. 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.
Data Analyst II employer: LexisNexis Risk Solutions
At ICIS, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters collaboration and accountability. Our commitment to employee well-being is reflected in our generous benefits package, extensive learning opportunities, and a supportive environment that encourages personal and professional growth. Join us in our mission to optimize the world's resources while enjoying a fulfilling career in a globally distributed team that values your insights and contributions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst II
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We think you need these skills to ace Data Analyst II
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!
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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.
