Senior Risk Analytics Developer

Job Title Risk Analytics Internal Audit Analyst Experience 4-6 years About the Company EY is a leading global professional services firm offering a broad range of services in assurance, tax, transaction, and advisory services. As part of EYs Risk Consulting practice, you will contribute to risk analytics and risk-driven AI solutions that support areas such as financial risk, regulatory compliance, internal controls, audit analytics, fraud detection, and enterprise risk management. Our mission is to design, build, and integrate scalable, secure, and auditable analytics platforms that enable clients to proactively identify, assess, and manage risk. Required Skills Expertlevel 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, and audit analytics concepts. Handson 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). AI: Understanding of Agentic Frameworks, Large Language Models (LLMs) (GPT, Claude, Llama, Gemini, etc.) Experience with RAG (Retrieval Augmented Generation) architectures. Knowledge of finetuning / parameterefficient tuning (LoRA, PEFT) Tools & Technologies: Strong SQL, Python, Power BI, Stream Lit Domain Expertise: Internal Audit and Risk Good to Have Strong understanding of AI Governance frameworks. Knowledge of ML Ops practices and tools (Kubeflow, Airflow, ML Flow). Exposure to big data ecosystems (Hadoop, Spark). Experience with containerization (Docker, Kubernetes).Strong understanding of data security and compliance in financial services. Good working knowledge of Alteryx and Power BI is preferred. Key Responsibilities Lead the design and development of Pythonbased AI/ML and advanced analytics solutions to support risk assessment, anomaly detection, control testing, and continuous risk monitoring. Architect, build, and optimize scalable data pipelines and workflows using Python, Alteryx, and distributed systems. Identify performance bottlenecks and implement optimizations to improve efficiency, reliability, and scalability.Enable risk analytics platforms that are explainable, auditable, and aligned with regulatory and governance requirements. Collaborate with risk consultants, architects, and crossfunctional 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 and enforce best practices, coding standards, and quality controls. Support delivery of highimpact risk analytics and automation initiatives across global engagements. To qualify for the role, you must have: Bachelors degree in computer science or related discipline; masters degree preferred. 36 years of relevant experience in Python development, AI/ML, and data engineering. What We Look For Working collaboratively in a team environment. Excellent oral and written communication skills. High attention to detail, particularly in risk, data accuracy, and controloriented contexts. Strong analytical and problemsolving skills. BE, BTech, MCA degree required. .