AI Data Scientist

About the Role

We’re looking for aData 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).