Data Scientist

LexisNexis; London; Hybrid; GBP 50,000 - 80,000; Full time

Job summary

LexisNexis is seeking a skilled Data Scientist to join their team, focusing on fraud detection using real-time data analysis. The role involves developing machine learning models and collaborating with various stakeholders to reduce fraud losses and enhance customer profitability in a fast-paced environment. Ideal candidates will have strong programming skills in SQL and Python, along with a passion for data-driven insights.

Qualifications

• Experience in a data science role in fraud, risk, or payments.
• Proficiency in Python and SQL.
• Hands-on experience with machine learning model development.

Responsibilities

• Develop and implement machine learning models for fraud detection.
• Define features that capture evolving fraudster behaviours.
• Deliver presentations and insights to executive audiences.

Skills

Data analysis

Statistical modelling

Machine learning

SQL

Python

Problem-solving

Attention to detail

Tools

SuperSet

Tableau

PowerBI

Job description

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, https://risk.lexisnexis.com

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

Learn more about the LexisNexis Risk team and how we work here

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