About the role
Requirements:
- 10-14 years of experience in data science, machine learning, advanced analytics, or related fields.
- Strong experience within banking, financial services, insurance, FinTech, InsurTech, or related domains.
- Proven experience building and deploying machine learning models in production environments.
- Demonstrated experience in fraud analytics, fraud detection, risk modelling, underwriting analytics, claims analytics, or related domains.
- Strong understanding of supervised and unsupervised learning techniques.
- Hands-on expertise in Python and common data science libraries (Pandas, Scikit-learn, XGBoost, LightGBM, TensorFlow, PyTorch, etc. ).
- Experience working with SQL and large-scale data platforms.
- Familiarity with cloud environments and modern MLOps practices.
- Strong communication, customer-facing, and stakeholder management skills.