Data Scientist (Machine Learning)

Job Description - Strong proficiency in programming languages such as Python, R, or Scala, as well as experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, SciPy). Solid understanding of statistical concepts and techniques, such as hypothesis testing, regression analysis, and time series forecasting. Experience with machine learning algorithms and frameworks (e.g., TensorFlow, Scikit-learn, PyTorch) for classification, regression, clustering, and anomaly detection. Knowledge of banking or financial services domains, including customer behavior modeling, credit risk assessment, fraud detection, and marketing analytics. Experience working with big data technologies and platforms (e.g., Hadoop, Spark, Kafka) is a plus. Excellent analytical and problem-solving skills, with the ability to work independently and collaboratively in a fast-paced environment. Strong communication and presentation skills, with the ability to convey technical concepts to non-technical stakeholders effectively. Proven track record of delivering high-quality, actionable insights and solutions that drive business impact in a banking or financial services context.