2068068-Senior Manager

EXL Talent Acquisition Team; Gurugram District; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

EXL Talent Acquisition Team is seeking a highly skilled Fraud Modelling Specialist to join our Risk Analytics team. You will build predictive models to detect and prevent fraudulent activity using Python and rigorous statistical methods.

You will collaborate with Risk, Engineering, and Product, monitor model performance, document methodologies, and stay updated on the latest fraud detection techniques.

Qualifications

• Bachelor’s or Master’s degree in CS, Statistics, Mathematics, or related field.
• Proven experience in fraud analytics or risk modeling.
• Strong Python skills with pandas, scikit-learn, NumPy, matplotlib.
• Experience across data preprocessing, feature engineering, model training, validation, deployment.
• Familiarity with SQL and data visualization is a plus.
• Strong problem-solving skills and attention to detail.

Responsibilities

• Design, develop, and deploy fraud detection models using ML and statistics.
• Analyze large datasets to identify fraud patterns and trends.
• Collaborate with Risk, Engineering, and Product for real-time prevention.
• Monitor model performance and recalibrate to maintain accuracy.
• Develop and maintain documentation for models and processes.
• Stay updated with advancements in fraud detection technologies.

Skills

Python

Pandas

Scikit-learn

NumPy

Matplotlib

SQL

Education

Bachelor's or Master's in CS/Statistics/Math

Tools

SQL

Job description

Job Summary

We are seeking a highly skilled and analytical Fraud Modelling Specialist to join our Risk Analytics team. The ideal candidate will have a strong background in data science, with hands‑on experience in developing predictive models to detect and prevent fraudulent activities. Proficiency in Python and a deep understanding of statistical modeling techniques are essential for this role.

Key Responsibilities

• Design, develop, and deploy fraud detection models using machine learning and statistical techniques.
• Analyze large datasets to identify fraud patterns and trends.
• Collaborate with cross-functional teams including Risk, Engineering, and Product to implement real‑time fraud prevention strategies.
• Continuously monitor model performance and recalibrate as needed to maintain accuracy and effectiveness.
• Develop and maintain robust documentation for models, methodologies, and processes.
• Stay updated with the latest advancements in fraud detection technologies and modeling techniques.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
• Proven experience in fraud analytics or risk modeling.
• Strong programming skills in Python, including libraries such as pandas, scikit‑learn, NumPy, and matplotlib.
• Experience with model development lifecycle: data preprocessing, feature engineering, model training, validation, and deployment.
• Familiarity with SQL and data visualization tools is a plus.
• Strong problem‑solving skills and attention to detail.

Preferred Qualifications

• Knowledge of anomaly detection, supervised and unsupervised learning techniques.
• Exposure to real‑time fraud detection systems.