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- Tasks: Analyze 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 a dynamic work environment with opportunities for innovation and collaboration.
- Why this job: Make a real-world impact while working with cutting-edge technology and global data.
- Qualifications: Experience in data science, proficiency in Python and SQL, and strong analytical skills required.
- Other info: Ideal for those who thrive in fast-paced settings and love tackling complex challenges.
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
- Appling 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
Learn more about the LexisNexis Risk team and how we work here
Data Scientist employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Familiarize yourself with the latest trends in fraud detection and risk management. Understanding the current landscape will help you speak confidently about how your skills can contribute to LexisNexis Risk Solutions.
✨Tip Number 2
Showcase your experience with machine learning and data analysis by preparing examples of past projects. Be ready to discuss how you approached problem-solving and the impact your work had on previous employers.
✨Tip Number 3
Network with professionals in the fraud and risk domain. Engaging with industry experts can provide insights into the challenges they face and how you can position yourself as a valuable asset to the team.
✨Tip Number 4
Prepare to demonstrate your proficiency in Python and SQL during interviews. Consider working on a small project or case study that highlights your technical skills and ability to analyze complex datasets.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and requirements. Highlight your relevant experience in data analysis, machine learning, and any specific tools mentioned like SQL and Python.
Tailor Your CV: Customize your CV to reflect your experience in fraud detection, risk assessment, and data science. Use keywords from the job description to ensure your application stands out to recruiters.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data science and your understanding of the fraud and risk domain. Mention specific projects or experiences that demonstrate your skills in machine learning and data analysis.
Prepare for Interviews: Be ready to discuss your technical skills in detail, especially your experience with Python and SQL. Prepare examples of how you've applied your problem-solving skills in previous roles, particularly in fast-paced environments.
How to prepare for a job interview at LexisNexis Risk Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and SQL in detail. Highlight specific projects where you developed machine learning models or worked on data analysis, as this will demonstrate your technical proficiency and relevance to the role.
✨Understand the Business Context
Familiarize yourself with LexisNexis Risk Solutions and their focus on fraud detection and risk assessment. Being able to articulate how your skills can contribute to their mission will show that you're not just technically capable but also aligned with their business goals.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially in relation to fraud detection and risk management. Practice articulating your thought process when faced with complex data challenges, as this will highlight your analytical skills.
✨Craft a Compelling Data Story
Since the role involves delivering presentations, prepare to discuss how you've effectively communicated insights from data in the past. Use examples that showcase your attention to detail and ability to create polished presentations for diverse audiences.
