Job Description:
About Us
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Global Business Services
Global Business Services delivers Technology and Operations capabilities to Lines of Business and Staff Support Functions of Bank of America through a centrally managed, globally integrated delivery model and globally resilient operations. Global Business Services is recognized for flawless execution, sound risk management, operational resiliency, operational excellence and innovation. In India, we are present in five locations and operate as BA Continuum India Private Limited (BACI), a non-banking subsidiary of Bank of America Corporation and the operating company for India operations of Global Business Services.
Process Overview
The Global Information Security (GIS) is responsible for protecting Bank information systems, confidential and proprietary data, and customer information. The team develops the Bank’s Information Security strategy and policy, manages the Information Security program and identifies and addresses vulnerabilities, Develops, deploys and manages a risk-based controls portfolio, Manages and operates global security operations center that monitor, detects and responds to cybersecurity incidents.
GIS Identity & Access management (IAM) Access Control Team goal is to ensure that the control processes and effectiveness are within the identified risk tolerance. Manage the performance and effectiveness of the working control through the establishment of metrics with thresholds. Validate the reasonability of Laws, Rules and Regulations mapping alignment to the controls, as aligned by the GIS Policy team.
Job Description
The Data Engineering Services team is seeking a hands-on IAM Data Scientist to deliver advanced analytics, AI/ML solutions, and data engineering capabilities that strengthen Identity and Access Management controls, governance, and risk reduction across the enterprise.
This role will require to transform complex access, entitlement, identity lifecycle, privileged access, and control data into actionable insights. The candidate will design and develop scalable data pipelines, predictive and detective analytics, AI/ML models, dashboards, and self-service reporting capabilities that help identify control gaps, access anomalies, toxic combinations, certification inefficiencies, and emerging IAM risks. The role requires strong technical depth in analytics, model development, model governance, AI risk management, and responsible AI practices, with the ability to convert data science outcomes into measurable control improvements and executive-ready risk narratives.
Responsibilities
- Lead advanced analytics and data science initiatives across IAM controls, access governance, entitlement management, privileged access, joiner-mover-leaver processes, access certifications, and policy adherence.
- Analyze large, complex, and disparate identity, access, entitlement, control, application, and audit datasets to identify trends, anomalies, control gaps, risk concentrations, and opportunities for automation.
- Design, build, validate, and tune AI/ML models for IAM use cases such as access anomaly detection, entitlement mining, role mining, toxic access identification, certification prioritization, privileged access monitoring, and control effectiveness measurement.
- Develop scalable data pipelines, feature engineering processes, reusable datasets, and analytics frameworks using Python, R, SQL, Splunk, Neo4j, and enterprise-approved data platforms.
- Design and maintain executive-ready dashboards, scorecards, and self-service reporting solutions that convert IAM control data into actionable insights for process owners, risk partners, and senior leadership.
- Embed model governance and AI risk controls into the analytics lifecycle, including documentation, model inventory, validation evidence, explainability, performance monitoring, drift detection, data lineage, reproducibility, and audit traceability.
- Assess and mitigate AI/ML risks including bias, privacy exposure, data quality limitations, explainability gaps, inappropriate automation, overfitting, and adversarial or unintended use of model outputs.
- Partner with IAM, GIS, cyber risk, audit, compliance, privacy, technology, and application teams to translate control requirements into measurable analytics solutions and governance outcomes.
- Drive process improvement and automation by identifying manual control activities, inefficient data handoffs, recurring exceptions, and opportunities to strengthen preventative and detective IAM controls.
- Prepare clear documentation, control evidence, methodology summaries, model performance updates, and risk narratives to support governance reviews, audit readiness, and management reporting.
Requirements
Education : B.E. / B. Tech/M.E. /M. Tech/B.Sc./M.Sc./BCA/MCA (prefer IT/CS specialization)
Certifications If Any : NA
Experience Range : 4+ years
Foundational skills
• Expertise in advanced data analytics and statistical modeling using Python, R, and SQL
• Proficiency in data visualization and graph analytics using Neo4j, Tableau, or equivalent tools
•Strong understanding of Identity Access Management architecture, technology and standards
• Strong quantitative analysis, data intuition, problem-solving, troubleshooting, and debugging skills
• Proficiency in AI, machine learning, data mining, feature engineering, and statistical analysis
• Excellent verbal and written communication, stakeholder management, documentation, and executive presentation skills
•Proven experience in end-to-end model development lifecycle including data preparation, feature engineering, model selection, training, validation, deployment readiness, monitoring, drift detection, and performance tuning
• Strong knowledge of model governance practices including model documentation, model inventory, model cards, approval workflows, control evidence, audit traceability, and alignment with enterprise risk management expectations
• Ability to identify, assess, and mitigate AI/ML risks including bias, explainability gaps, privacy exposure, data quality issues, model drift, overfitting, adversarial misuse, and inappropriate automation of access decisions
• Experience applying AI/ML techniques to IAM datasets such as entitlement mining, access anomaly detection, role mining, toxic access identification, privileged access monitoring, joiner-mover-leaver patterns, and access certification optimization
Desired skills
• Experience with data storytelling and reporting design that helps stakeholders make actionable control and risk decisions
• Experience building dashboards or graph-based analysis views using Tableau, Neo4j, or similar platforms
• Able to prioritize and execute tasks in a fast-paced environment
• Experience with MLOps practices and tools such as MLflow, model registry, CI/CD for analytics, automated model testing, experiment tracking, monitoring dashboards, and controlled promotion of models across environments
• Exposure to generative AI, large language models, prompt evaluation, retrieval-augmented generation concepts, and safe use of AI assistants for control evidence summarization, policy mapping, and IAM insights
Work Timings : 11:30 Am to 8:30 Pm
Job Location : Hyderabad, Mumbai
