We are seeking a talented and motivated Banking Data Scientist to join our growing analytics team. In this role, you will leverage advanced statistical techniques, machine learning models, and data-driven insights to support strategic decision-making across various banking functions, including risk management, customer analytics, fraud detection, lending, and operational efficiency.
## Key Responsibilities
- Develop, implement, and maintain predictive and prescriptive analytics models
- Analyze large and complex datasets to identify trends, patterns, and business opportunities
- Support credit risk, fraud detection, customer segmentation, and portfolio optimization initiatives
- Collaborate with business stakeholders to translate business challenges into analytical solutions
- Design and monitor machine learning models throughout their lifecycle
- Build dashboards and reporting solutions to communicate insights effectively
- Ensure data quality, governance, and compliance with banking regulations
- Present findings and recommendations to both technical and non-technical audiences
## Required Qualifications
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Finance, or a related quantitative field
- Minimum of 1 year of hands-on experience as a Data Scientist, preferably within banking, financial services, fintech, or a highly regulated environment
- Strong knowledge of statistical analysis, predictive modeling, and machine learning techniques
- Proficiency in Python and/or R
- Experience with SQL and working with large-scale datasets
- Familiarity with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or similar
- Experience with data visualization tools such as Power BI, Tableau, or similar
- Strong analytical thinking and problem-solving skills
- Excellent communication and stakeholder management abilities
## Preferred Qualifications
- Experience in banking domains such as credit risk, anti-money laundering (AML), fraud analytics, customer analytics, or regulatory reporting
- Knowledge of cloud platform Azure
- Understanding of banking regulations and risk frameworks
- Experience with MLOps, model monitoring, and deployment practices