Risk Analytics Engineer- Python Senior

As a Risk Analytics Engineer- Python Senior at EY, you will have the opportunity to contribute to Risk Analytics and risk-driven AI solutions in areas such as financial risk, regulatory compliance, internal controls, audit analytics, fraud detection, and enterprise risk management. Your role will involve designing, building, and integrating scalable, secure, and auditable analytics platforms to help clients proactively identify, assess, and manage risk. Key Responsibilities: - Lead the design and development of Python-based AI/ML and advanced analytics solutions for risk assessment, anomaly detection, control testing, and continuous risk monitoring. - Architect, build, and optimize scalable data pipelines and workflows using PySpark, Alteryx, and distributed systems. - Enable risk analytics platforms that are explainable, auditable, and compliant with regulatory and governance requirements. - Collaborate with risk consultants, architects, and cross-functional teams to translate risk and business requirements into technical solutions. - Identify technology and data risks, propose mitigation strategies, and ensure solution robustness. - Mentor junior engineers, enforce best practices, coding standards, and quality controls. - Support the delivery of high-impact risk analytics and automation initiatives across global engagements. Required Skills: - Expert-level proficiency in Python programming and software design principles. - Experience designing risk analytics pipelines, including data ingestion, transformation, validation, and monitoring. - Awareness of risk, controls, compliance, fraud, or audit analytics concepts. - Strong experience in data engineering using PySpark, Alteryx, and distributed systems. - Hands-on experience with microservices architecture and CI/CD pipelines. - Proficiency in SQL, database performance tuning, and data governance. - Familiarity with cloud platforms (Azure preferred, AWS/GCP optional). Good to Have: - Advanced experience with AI/ML techniques. - Knowledge of MLOps practices and tools (Kubeflow, Airflow). - Exposure to big data ecosystems (Hadoop, Spark). - Experience with containerization (Docker, Kubernetes). - Strong understanding of data security and compliance in financial services. To qualify for this role, you must have a Bachelors degree in Computer Science or related discipline; a Masters degree is preferred, along with 36 years of relevant experience in Python development, AI/ML, and data engineering. At EY, the focus is on building a better working world by creating long-term value for clients, people, and society, as well as building trust in the capital markets. EY teams in over 150 countries work collaboratively to provide trust through assurance and help clients grow, transform, and operate in various domains such as assurance, consulting, law, strategy, tax, and transactions. As a Risk Analytics Engineer- Python Senior at EY, you will have the opportunity to contribute to Risk Analytics and risk-driven AI solutions in areas such as financial risk, regulatory compliance, internal controls, audit analytics, fraud detection, and enterprise risk management. Your role will involve designing, building, and integrating scalable, secure, and auditable analytics platforms to help clients proactively identify, assess, and manage risk. Key Responsibilities: - Lead the design and development of Python-based AI/ML and advanced analytics solutions for risk assessment, anomaly detection, control testing, and continuous risk monitoring. - Architect, build, and optimize scalable data pipelines and workflows using PySpark, Alteryx, and distributed systems. - Enable risk analytics platforms that are explainable, auditable, and compliant with regulatory and governance requirements. - Collaborate with risk consultants, architects, and cross-functional teams to translate risk and business requirements into technical solutions. - Identify technology and data risks, propose mitigation strategies, and ensure solution robustness. - Mentor junior engineers, enforce best practices, coding standards, and quality controls. - Support the delivery of high-impact risk analytics and automation initiatives across global engagements. Required Skills: - Expert-level proficiency in Python programming and software design principles. - Experience designing risk analytics pipelines, including data ingestion, transformation, validation, and monitoring. - Awareness of risk, controls, compliance, fraud, or audit analytics concepts. - Strong experience in data engineering using PySpark, Alteryx, and distributed systems. - Hands-on experience with microservices architecture and CI/CD pipelines. - Proficiency in SQL, database performance tuning, and data governance. - Familiarity with cloud platforms (Azure preferred, AWS/GCP optional). Good to Have: - Advanced experience with AI/ML techniques. - Knowledge of MLOps practices and tools (Kubeflow, Airflow). - Exposure to b