Risk Analytics Engineer- Python Staff
EY-Parthenon
All India, Bangalore • 1 month ago
Experience: 1 to 5 Yrs
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Job Description
As a Risk Analytics Engineer- Python Staff at EY, you will have the opportunity to contribute to risk-driven AI and data solutions supporting financial risk, regulatory compliance, internal controls, audit analytics, and enterprise risk management. Your responsibilities will include designing and developing Python-based AI/ML solutions, building and maintaining data pipelines using tools like PySpark and Alteryx, collaborating with cross-functional teams, and ensuring adherence to EY standards and quality KPIs. Your unique voice and perspective will help EY become even better and contribute to building a better working world for all.
**Key Responsibilities:**
- Design and develop Python-based AI/ML solutions for risk assessment, anomaly detection, control testing, and automation.
- Build, optimize, and maintain data pipelines and workflows using PySpark, Alteryx, and related technologies.
- Collaborate with risk consultants and cross-functional teams to deliver high-quality, risk-aligned solutions.
- Support risk-driven AI transformation initiatives to ensure models are explainable, auditable, and compliant.
- Estimate technical effort, identify delivery and technology risks, and propose mitigation strategies.
- Ensure adherence to EY standards, methodologies, governance, and quality KPIs.
- Proactively identify issues related to data quality, model performance, or controls and support resolution.
**Qualifications Required:**
- Strong proficiency in Python programming.
- Awareness of risk, controls, compliance, or audit analytics concepts.
- Experience with data processing tools such as PySpark, Alteryx, and ETL pipelines.
- Excellent problem-solving and debugging skills.
- Ability to understand business and risk requirements and translate them into technical solutions.
Join EY and be part of a team that is dedicated to building a better working world through innovative solutions and a culture of inclusivity and support. As a Risk Analytics Engineer- Python Staff at EY, you will have the opportunity to contribute to risk-driven AI and data solutions supporting financial risk, regulatory compliance, internal controls, audit analytics, and enterprise risk management. Your responsibilities will include designing and developing Python-based AI/ML solutions, building and maintaining data pipelines using tools like PySpark and Alteryx, collaborating with cross-functional teams, and ensuring adherence to EY standards and quality KPIs. Your unique voice and perspective will help EY become even better and contribute to building a better working world for all.
**Key Responsibilities:**
- Design and develop Python-based AI/ML solutions for risk assessment, anomaly detection, control testing, and automation.
- Build, optimize, and maintain data pipelines and workflows using PySpark, Alteryx, and related technologies.
- Collaborate with risk consultants and cross-functional teams to deliver high-quality, risk-aligned solutions.
- Support risk-driven AI transformation initiatives to ensure models are explainable, auditable, and compliant.
- Estimate technical effort, identify delivery and technology risks, and propose mitigation strategies.
- Ensure adherence to EY standards, methodologies, governance, and quality KPIs.
- Proactively identify issues related to data quality, model performance, or controls and support resolution.
**Qualifications Required:**
- Strong proficiency in Python programming.
- Awareness of risk, controls, compliance, or audit analytics concepts.
- Experience with data processing tools such as PySpark, Alteryx, and ETL pipelines.
- Excellent problem-solving and debugging skills.
- Ability to understand business and risk requirements and translate them into technical solutions.
Join EY and be part of a team that is dedicated to building a better working world through innovative solutions and a culture of inclusivity and support.
Skills Required
Risk
compliance
Alteryx
Spark
Tableau
Azure
GCP
Python programming
controls audit analytics concepts
Data processing tools such as PySpark
ETL pipelines
Problemsolving
debugging skills
Understanding business
risk requirements
AIML frameworks like TensorFlow
PyTorch
Scikitlearn
Big data ecosystems like Hadoop
Data visualization tools like Power BI
Microservices architecture
CICD pipelines
Cloud platforms like AWS
Posted on: March 3, 2026
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