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For Companies At a Glance
- Tasks: Join a dynamic team to tackle real-world business challenges using data science and analytics.
- Company: LexisNexis Risk Solutions, a leader in risk assessment and insurance analytics.
- Benefits: Enjoy private medical benefits, wellbeing programs, and extensive learning resources.
- Why this job: Make an impact by driving data-driven decisions across the insurance lifecycle.
- Qualifications: Experience in data science, proficiency in SQL, and knowledge of Python or R.
- Other info: Collaborative environment with opportunities for mentoring and career growth.
The predicted salary is between 43200 - 72000 ÂŁ per year.
About the Business
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 dataâinformed decisionâmaking.
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 realâworld business challenges, contribute to new and existing products, and communicate insights clearly to a wide range of audiences.
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, highâvalue use cases
- Work collaboratively with technology, product, and data engineering teams to deliver reliable, productionâready solutions
- Communicate analytical findings clearly to both technical and nonâtechnical stakeholders
- Support project planning, including requirements, timelines, and delivery
- Help improve analytics platforms and cloudâbased workflows, including testing and migration activities
- Use a combination of openâsource 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 semiâstructured 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 cloudâbased 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.
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: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice đ¤Ť
We think this is how you could land Senior Data Scientist
â¨Tip Number 1
Network like a pro! Reach out to current employees at LexisNexis Risk Solutions on LinkedIn. Ask them about their experiences and any tips they might have for the interview process. Personal connections can give you an edge!
â¨Tip Number 2
Prepare for your interviews by brushing up on your data science skills. Be ready to discuss your experience with SQL, Python, and machine learning. Practise explaining complex concepts in simple terms, as you'll need to communicate with both technical and non-technical folks.
â¨Tip Number 3
Showcase your projects! Bring examples of your previous work to the interview. Whether it's a data analysis project or a machine learning model, having tangible evidence of your skills can really impress the hiring team.
â¨Tip Number 4
Don't forget to apply through our website! Itâs the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the team at LexisNexis Risk Solutions.
We think you need these skills to ace Senior Data Scientist
Some tips for your application đŤĄ
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 what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Keep it concise but engaging â we love a good story!
Showcase Your Technical Skills: Donât forget to mention your proficiency in SQL and programming languages like Python or R. Weâre keen to see how youâve applied these skills in real-world scenarios, so give us some examples!
Apply Through Our Website: We encourage you to apply directly through our website. Itâs the best way to ensure your application gets into the right hands. Plus, it shows us youâre serious about joining our team!
How to prepare for a job interview at LexisNexis Risk Solutions
â¨Know Your Data Science Stuff
Make sure you brush up on your data science fundamentals, especially in SQL and programming languages like Python or R. Be ready to discuss your experience with data extraction, cleaning, and transformation, as well as any machine learning projects you've worked on.
â¨Show Off Your Problem-Solving Skills
Prepare to talk about specific business challenges you've tackled using data analytics. Think of examples where you designed analytical solutions or explored new datasets, and be ready to explain your thought process and the impact of your work.
â¨Communicate Like a Pro
Since you'll need to communicate complex ideas to both technical and non-technical stakeholders, practice explaining your past projects in simple terms. Use clear, concise language and avoid jargon when possible to ensure everyone understands your insights.
â¨Collaborate and Contribute
Highlight your teamwork skills and experiences. Be prepared to discuss how you've worked with cross-functional teams, such as technology and product teams, to deliver reliable solutions. Mention any mentoring experiences you have, as this shows your willingness to support colleagues.