🛠 Tech Stack

💼 About This Role

You'll design and deploy advanced machine learning models to detect and prevent fraud across global payment systems. You will own the full ML lifecycle from problem definition to deployment, directly protecting users and financial infrastructure. This high-visibility role offers the chance to build end-to-end risk algorithms in a collaborative, product-driven environment.

🎯 What You'll Do

• Develop and operationalize ML solutions for fraud and risk challenges.
• Translate business challenges into ML problems and scalable solutions.
• Build, train, and deploy ML models with advanced feature engineering.
• Analyze fraud patterns and collaborate with cross-functional teams.
• Monitor model performance and iterate based on evolving risks.

📋 Requirements

• 3+ years experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or Keras.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or related field.
• Strong Python programming skills for data manipulation and model development.
• Experience in payment risk, fraud detection, or e-commerce risk is a strong plus.

✨ Nice to Have

• Exposure to applying ML or LLM-based approaches to real-time systems.
• Experience working in cross-functional teams in a product-driven environment.
• Strong analytical thinking and problem-solving skills.

🎁 Benefits & Perks

• 💰 Competitive compensation including base salary, bonus, and equity.
• 🏥 Comprehensive medical, dental, and vision insurance (for eligible employees).
• 🏖️ Paid time off including vacation days and company holidays.
• 📈 Retirement savings plan and additional financial wellness benefits.
• 🌍 Opportunity to work on high-impact global financial risk and fraud systems.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min