Data Scientist Banking

• 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.

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.

This is an excellent opportunity for a data professional who has already gained practical experience within data science and is looking to further develop their career in the banking and financial services sector., * 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., * 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.