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- Tasks: Analyse data and develop machine learning models to combat fraud and enhance customer experience.
- Company: Join LexisNexis Risk Solutions, a leader in risk assessment and fraud detection.
- Benefits: Enjoy generous holidays, health benefits, and extensive learning resources.
- Other info: Collaborate with diverse teams in a fast-paced environment with excellent career growth opportunities.
- Why this job: Make a real-world impact by protecting billions in revenue from fraud.
- Qualifications: Experience in data science, proficiency in Python and SQL, and strong analytical skills.
The predicted salary is between 50000 - 70000 £ per year.
About the business: LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management.
About the team: You will be part of a team who use global data from the largest real-time fraud detection platform to craft solutions for our enterprise customers.
About the role: Your experience with data analysis, statistical modelling, and machine learning will lead to immediate real-world impact in the form of lower customer friction, reduced fraud losses and as a result, increased customer profitability. You’ll leverage a real-time platform analysing billions of transactions per month for some of the largest companies operating in Financial Services, Insurance, e-Commerce, and On-Demand Services. These tools will allow you to attain a unique perspective of the Internet, and every persona connected to it. On top of driving innovation projects, you’ll be continually collaborating with internal product and engineering teams, customer-facing account teams, and external business leaders and risk managers. The comprehensive models you build will go head-to-head against some of the most motivated attackers in the world to protect billions in revenue.
Responsibilities:
- Scoping, developing, and implementing machine learning or rule-based models following best practice, to banking model governance standards.
- Using your strong knowledge of SQL and Python plus quantitative skills to define features that capture evolving fraudster behaviours.
- Develop internal tools to streamline the model training pipeline and analytics workflows.
- Applying your curiosity and problem-solving skills to transform uncertainty into value-add opportunities.
- Using your strong attention to detail and ability to craft a story through data, delivering industry-leading presentations for external and executive audiences.
- Building an extensive knowledge of cybercrime – account takeover, scams, social engineering, Card Not Present (CNP) fraud, money laundering and mule fraud etc.
- Employing your multi-tasking and prioritisation skills to excel in a fast-paced environment with frequently changing priorities.
Requirements:
- Experience in a data science role, ideally within the fraud, risk, or payments domain.
- Proficiency in Python and SQL (BI tools such as SuperSet, Tableau or PowerBI is a bonus).
- Hands-on experience in machine learning model development, evaluation, and production deployment, with familiarity in MLOps principles to build scalable and standardised workflows and implement effective ML monitoring systems.
- Proven ability to create polished presentations and effectively communicate insights to customers with attention to detail.
- Have extensive multi-tasking and prioritisation skills. Needs to excel in fast paced environment with frequently changing priorities.
Working for you:
- Generous holiday allowance with the option to buy additional days.
- Health screening, eye care vouchers and private medical benefits.
- Wellbeing programs.
- Life Assurance.
- Access to a competitive contributory pension scheme.
- Save As You Earn share option scheme.
- Travel Season ticket loan.
- Electric Vehicle Scheme.
- Optional Dental Insurance.
- Maternity, paternity and shared parental leave.
- Employee Assistance Programme.
- Access to emergency care for both the elderly and children.
- 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.
- Access to employee discounts scheme via Perks at Work.
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 Scientist in London employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at LexisNexis Risk Solutions. A friendly chat can sometimes lead to job opportunities that aren't even advertised!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data analysis projects, especially those related to fraud detection or risk management. This will give you an edge and demonstrate your hands-on experience.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and Python skills. Be ready to discuss your previous projects and how you've tackled real-world problems. Practice explaining complex concepts in simple terms – it’s all about storytelling!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with data analysis, machine learning, 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 tell us why you're the perfect fit for our team. Share your passion for data science and how you can contribute to tackling fraud and risk challenges. Keep it engaging and personal!
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Python and SQL! If you have experience with BI tools like Tableau or PowerBI, make sure to include that too. We love seeing candidates who can hit the ground running with their technical expertise.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our company culture there!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Data Science Stuff
Make sure you brush up on your data analysis, statistical modelling, and machine learning skills. Be ready to discuss specific projects where you've applied these skills, especially in fraud detection or risk management. This will show that you can hit the ground running!
✨Master SQL and Python
Since proficiency in SQL and Python is crucial for this role, practice coding challenges and be prepared to demonstrate your knowledge during the interview. You might even get asked to solve a problem on the spot, so keep your skills sharp!
✨Craft Your Story with Data
Prepare to present your past work in a way that tells a compelling story. Use data visualisation tools like Tableau or PowerBI to showcase your findings. This will not only highlight your technical skills but also your ability to communicate insights effectively.
✨Stay Curious and Problem-Solving
Showcase your curiosity and problem-solving mindset by discussing how you've tackled complex issues in the past. Think of examples where you turned uncertainty into actionable insights, especially in fast-paced environments. This will demonstrate your fit for the dynamic nature of the role.