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.
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).