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- Tasks: Develop and implement 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 a competitive pension scheme.
- Other info: Dynamic team environment with opportunities for personal growth and community involvement.
- 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 60000 - 80000 £ 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: 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.
Data Marketing Scientist employer: LexisNexis Risk Solutions
Contact Detail:
LexisNexis Risk Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Marketing Scientist
✨Tip Number 1
Network like a pro! Reach out to current employees at LexisNexis Risk Solutions on LinkedIn. A friendly chat can give us insights into the company culture and maybe even a referral!
✨Tip Number 2
Prepare for the interview by brushing up on your data analysis skills. Be ready to discuss your experience with SQL and Python, and have examples of your machine learning projects at the ready. We want to see your passion shine through!
✨Tip Number 3
Showcase your storytelling abilities with data! When you present your past work, focus on how your insights led to real-world impacts. This is key for impressing the team at LexisNexis Risk Solutions.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to engage with us directly.
We think you need these skills to ace Data Marketing Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Marketing Scientist role. Highlight your experience with data analysis, machine learning, and any relevant projects that showcase your skills in Python and SQL. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you're the perfect fit for this role. Share your passion for data science and fraud prevention, and don’t forget to mention any specific experiences that align with our mission at LexisNexis Risk Solutions.
Showcase Your Problem-Solving Skills: In your application, give examples of how you've tackled complex problems in the past. We love candidates who can turn uncertainty into opportunities, so share those stories that demonstrate your analytical thinking and creativity!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets to the right people. Plus, it shows us you’re serious about joining our team at LexisNexis Risk Solutions!
How to prepare for a job interview at LexisNexis Risk Solutions
✨Know Your Data Inside Out
Make sure you brush up on your data analysis skills, especially in SQL and Python. Be prepared to discuss specific projects where you've used these tools to solve real-world problems, particularly in fraud or risk contexts.
✨Showcase Your Machine Learning Expertise
Be ready to talk about your experience with machine learning model development. Highlight any projects where you've implemented models that had a tangible impact, and be prepared to explain your approach to model governance and MLOps principles.
✨Craft a Compelling Story with Data
Practice presenting your findings in a clear and engaging way. Use examples from your past work to demonstrate how you can turn complex data into actionable insights, especially for non-technical audiences.
✨Demonstrate Your Problem-Solving Skills
Prepare to discuss how you've tackled uncertainty in previous roles. Think of specific instances where your curiosity led to innovative solutions, and be ready to share how you prioritise tasks in fast-paced environments.