Data Scientist

Risk Solution Group; London; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading company in risk assessment seeks a Data Scientist to leverage machine learning and data analysis to combat fraud. This role involves developing models, collaborating with teams, and presenting insights to enhance customer experience and reduce losses. Join a diverse team committed to innovation and operational efficiency.

Qualifications

• Experience in data science roles, preferably in fraud, risk, or payments sectors.
• Hands-on experience with machine learning model development and MLOps principles.

Responsibilities

• Design and implement machine learning or rule-based models.
• Utilize SQL and Python to develop features that detect fraud patterns.
• Deliver presentations highlighting data-driven insights.

Skills

Data Analysis

Statistical Modeling

Machine Learning

Problem Solving

Presentation Skills

Tools

Python

SQL

Tableau

PowerBI

Job description

About the business: LexisNexis Risk Solutions is a key partner in risk assessment. Within our Business Services vertical, we offer solutions that help businesses drive revenue, improve operational efficiency, and enhance customer experience. Our solutions address challenges in Anti-Money Laundering, Identity Verification, Fraud Prevention, and Customer Data Management. Learn more at https://risk.lexisnexis.com.

About the team: You will join a team utilizing global data from our real-time fraud detection platform to develop solutions for enterprise clients.

About the role: Your expertise in data analysis, statistical modeling, and machine learning will have a direct impact by reducing customer friction, lowering fraud losses, and increasing profitability. You'll work with a platform analyzing billions of transactions monthly across sectors like Financial Services, Insurance, e-Commerce, and On-Demand Services. This role involves collaborating with product, engineering, and business teams, and building models to combat sophisticated fraud attacks.

Responsibilities:

1. Design and implement machine learning or rule-based models adhering to best practices and governance standards.
2. Utilize SQL and Python, along with your quantitative skills, to develop features that detect evolving fraud patterns.
3. Create internal tools to optimize model training and analytics workflows.
4. Apply problem-solving skills to turn uncertainties into actionable insights.
5. Deliver compelling presentations to internal and external stakeholders, highlighting data-driven insights.
6. Develop expertise in cybercrime types such as account takeover, scams, social engineering, CNP fraud, and money laundering.
7. Manage multiple priorities effectively in a dynamic environment.

Requirements:

1. Experience in data science roles, preferably in fraud, risk, or payments sectors.
2. Proficiency in Python and SQL; experience with BI tools like Tableau, PowerBI, or SuperSet is advantageous.
3. Hands-on experience with machine learning model development, evaluation, deployment, and familiarity with MLOps principles for scalable workflows and monitoring.
4. Strong presentation skills and the ability to communicate insights clearly and effectively.
5. Excellent multitasking and prioritization skills in a fast-paced setting.

Learn more about the LexisNexis Risk team and our work here.

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