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- Tasks: Analyse data and develop machine learning models to combat fraud in real-time.
- Company: Join LexisNexis Risk Solutions, a leader in risk assessment and fraud prevention.
- Benefits: Enjoy generous holidays, health perks, and a competitive pension scheme.
- Why this job: Make a real-world impact while collaborating with innovative teams in a fast-paced environment.
- Qualifications: Experience in data science, proficiency in Python and SQL, and strong presentation skills required.
- Other info: Access extensive learning resources and volunteer opportunities to support causes you care about.
The predicted salary is between 36000 - 60000 £ 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. You can learn more about LexisNexis Risk at the link below,
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
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:
- 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
Learn more about the LexisNexis Risk team and how we work here
Data Scientist - Fraud employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Fraud
✨Tip Number 1
Familiarise yourself with the latest trends in fraud detection and prevention. Understanding the current landscape of cybercrime, including account takeover and money laundering, will help you speak confidently about relevant issues during interviews.
✨Tip Number 2
Brush up on your SQL and Python skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source projects that involve data analysis or machine learning to showcase your abilities.
✨Tip Number 3
Prepare to discuss your experience with machine learning model development. Be ready to explain your approach to building, evaluating, and deploying models, as well as any challenges you've faced and how you overcame them.
✨Tip Number 4
Practice your presentation skills, as you'll need to communicate complex data insights effectively. Create a few mock presentations based on hypothetical data scenarios to demonstrate your ability to craft a compelling narrative through data.
We think you need these skills to ace Data Scientist - Fraud
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in fraud, risk, or payments. Emphasise your proficiency in Python and SQL, as well as any hands-on experience with machine learning model development.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your skills and experiences align with the responsibilities outlined in the job description, particularly your ability to communicate insights effectively and your attention to detail.
Showcase Your Projects: If you have worked on relevant projects, especially those involving fraud detection or machine learning, include them in your application. Provide specific examples of how your work has led to tangible results, such as reduced fraud losses or improved customer experiences.
Prepare for Technical Questions: Be ready to discuss your technical skills in detail, particularly your experience with SQL and Python. Prepare to explain your approach to developing and implementing machine learning models, and be ready to share insights from your past work that demonstrate your problem-solving abilities.
How to prepare for a job interview at LexisNexis Risk Solutions
✨Showcase Your Technical Skills
Make sure to highlight your proficiency in Python and SQL during the interview. Be prepared to discuss specific projects where you've applied these skills, especially in the context of fraud detection or risk management.
✨Demonstrate Your Problem-Solving Ability
Prepare examples that showcase your curiosity and problem-solving skills. Discuss how you've transformed uncertainty into actionable insights, particularly in fast-paced environments where priorities shift frequently.
✨Communicate Effectively
Since you'll be presenting to both technical and non-technical audiences, practice delivering clear and polished presentations. Focus on how you can craft a compelling story through data, making complex concepts accessible.
✨Understand Cybercrime Trends
Familiarise yourself with current trends in cybercrime, such as account takeover and money laundering. Being able to discuss these topics will demonstrate your extensive knowledge and commitment to the field of fraud prevention.
