AI Data Scientist

## Description

### **About the Role**

We’re looking for a **Data Scientist with deep AI and machine learning expertise** to help shape the future of data-driven innovation in fintech. You’ll work on developing intelligent systems that power risk modeling, fraud prevention, customer insights and targeting, and payment optimization. Your models will have a direct impact on financial decisions, operational efficiency, and customer trust across our products.

### **Key Responsibilities**

• **AI-Driven Insights:** Develop and deploy advanced machine learning models to optimize customer targeting, payment monitoring and growth and operational efficiency opportunities.
• **Predictive Modeling:** Build forecasting models to improve transaction accuracy, detect anomalies, and assess financial risk.
• **Data Engineering & Feature Design:** Clean, transform, and model large, high-velocity financial datasets with attention to data integrity and compliance.
• **AI Product Integration:** Collaborate with Product to integrate AI solutions into production systems for real-time financial decisioning.
• **Experimentation:** Lead A/B tests and model performance evaluations to validate model effectiveness and regulatory compliance.
• **Communication:** Translate technical findings into actionable insights for business leaders and compliance teams.
• **Research & Innovation:** Stay on top of advancements in generative AI, LLMs, and financial AI applications to guide innovation strategy.

## Qualifications

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or related field.
• 3+ years of experience in a data science or AI-focused role within fintech, banking, or payments.
• Expertise in Python, machine learning frameworks (scikit-learn, TensorFlow, PyTorch), and data pipelines.
• Strong background in supervised/unsupervised learning, anomaly detection, NLP, and generative AI.
• Familiarity with financial data structures, regulatory standards (e.g., PCI-DSS, GDPR), and model governance.
• Experience with cloud platforms such as Snowflake for ML deployment.

Preferred Qualifications

• Experience in fraud analytics, risk scoring, or payment decision models.
• Understanding of MLOps and continuous model monitoring in regulated environments.
• Familiarity with financial transaction data, open banking APIs, or real-time payments systems.
• Experience developing LLM-powered assistants or AI copilots for financial operations or support.
• Strong data storytelling and visualization skills (Tableau preferred).