Manager - Data Analytics and Fraud Prevention

Overview

Bank of America is dedicated to enhancing financial lives through responsible growth and inclusive culture. We promote an engaging workplace supporting career advancement while emphasizing wellbeing and diversity. Our Global Business Services (GBS) division provides essential technology and operations services globally, recognized for operational excellence and innovation.

Role Summary

We are expanding our Strategies, Analytics & Process Integration team in India, focusing on improving fraud detection and minimizing losses.

Key Responsibilities

• Utilize Python and PySpark extensively to build, optimize, and maintain scalable data pipelines leveraging big data frameworks such as Spark and Hadoop.
• Design and manage complete data ingestion and transformation workflows for processing complex datasets, ensuring readiness for analytics and modeling.
• Automate data workflows eliminating manual repetition by implementing scheduling, monitoring, and error recovery through Python/PySpark and orchestration tools.
• Create and uphold dependable data infrastructures that support reporting, analytics, machine learning, and fraud detection models.
• Develop comprehensive data validation, quality checks, and anomaly detection to maintain dataset accuracy and reliability.
• Architect and support low-latency data pipelines enabling near real-time data access for operational decisions.
• Work in close collaboration with data scientists, product managers, and stakeholders to align on data requirements and strategies, ensuring unified customer-level datasets across systems.
• Partner with leadership to develop data strategies that focus on client protection, real-time data availability, and comprehensive customer views for intelligent fraud decision-making.

Required Qualifications and Experience

• Advanced degree in Statistics, Mathematics, Applied Sciences, Engineering, or related disciplines from a reputed institution.
• 5 to 8 years of relevant analytics experience, with at least 2 years in data engineering using PySpark and big data technologies.
• Expertise in Python, PySpark, and SQL for data processing and analysis.
• Solid understanding of big data ecosystems, graph databases, and query languages such as GSQL, Cypher, and Hive preferred.
• Experience in the U.S. financial services sector and knowledge of domains like Fraud, Compliance, and Risk is advantageous.
• Proven record of designing and deploying analytical solutions generating significant financial impact, combined with strong management and communication skills.
• Advanced knowledge of SQL and foundational statistical concepts.
• Familiarity with software tools like HUE, Hive, and other data gathering platforms.

Work Schedule and Location

Working hours are either 11:30 AM to 8:30 PM or 12:30 PM to 9:30 PM. This position is based onsite in Mumbai, India.