Data Scientist - Python , PySpark

Description: We are looking for an experienced Senior Data Scientist with strong expertise in Python, PySpark, and advanced analytics, along with a solid understanding of Financial Crime, Fraud Monitoring, and AML concepts. The ideal candidate will work on large-scale data to build, enhance, and optimize analytical and machine learning models used for fraud detection and financial crime prevention. Design, develop, and deploy data science and machine learning models for fraud detection, transaction monitoring, and financial crime use cases Analyze large, complex datasets using Python and PySpark in distributed data environments Build end-to-end analytics pipelines including data ingestion, feature engineering, model training, and validation Apply statistical analysis, ML techniques, and pattern recognition to identify suspicious behaviors and emerging fraud typologies Collaborate with business, compliance, and technology teams to translate financial crime requirements into analytical solutions Monitor model performance, perform tuning, and ensure model stability and regulatory alignment Document models, methodologies, and assumptions for internal governance and audit requirements Stay updated on financial crime trends, fraud patterns, and regulatory expectations Required Skills & Qualifications 5+ years of experience in Data Science, Analytics, or a related role Strong proficiency in Python (NumPy, Pandas, Scikit-learn, etc.) Hands-on experience with PySpark / Spark for large-scale data processing Solid understanding of Financial Crime domains including: Fraud Monitoring Transaction Monitoring AML / CTF concepts Customer risk and suspicious activity patterns Experience building and validating machine learning models (supervised & unsupervised) Strong knowledge of data preprocessing, feature engineering, and model evaluation Ability to communicate complex analytical findings to non-technical stakeholders