Senior Associate - Risk Management

New York Life Insurance Co•City of White Plains, NY

29d•Onsite

About The Position

This role involves conducting cybersecurity risk assessments and control effectiveness assessments over critical applications, infrastructure, and enterprise processes. The position will perform compliance validations against controls derived from regulations such as NYDFS, SOX, and MAR, ensuring proper implementation through evidence analysis. A key responsibility is designing an AI Governance model for securing AI assets, including inventorying, risk and control assessments, and reporting. The role also includes creating a knowledge management AI model that consumes company risk and control data to answer queries in natural language, and developing a model capable of answering in-depth questions from various audience groups. Additionally, the position will create a protected landscape for information exchanges, streamline and automate cybersecurity residual risk and control effectiveness reporting by designing risk measurement methodologies, and develop automated tableau-based dashboards. The role requires applying knowledge of AWS and DBMS to implement underlying AWS databases and connections to Tableau.

Requirements

Master's degree in Cybersecurity, Computer Science, or related field (willing to accept foreign education equivalent) plus four (4) years of experience as a Senior Associate – Risk Management or related occupation conducting cybersecurity assessments, compliance management, reporting, and developing and automating security testing processes.
Alternatively, a Bachelor’s degree in Cybersecurity, Computer Science or related field (willing to accept foreign education equivalent) plus 6 years of experience as a Senior Associate - Risk Management or related occupation conducting cybersecurity assessments, compliance management, reporting, and developing and automating security testing processes.
Experience applying risk and control domain knowledge for Identity and Access Management (IAM), Vulnerability Management (VM), Logging and Monitoring (L&M), data protection, and cyber operations to develop risk measurement methodologies.
Experience automating control implementation and managing effectiveness through assessments to ensure compliance and risk mitigation.
Experience implementing onboarding/termination controls, privileged access controls, and role-based access controls.
Experience designing and evaluating secure architectures for complex IT environments, focusing on hybrid infrastructures that integrate on-premises and cloud-based solutions.
Experience utilizing industry standards and frameworks, including the NIST Cybersecurity Framework, ISO 27001, and NIST SP 800-37 & 800-53, to guide security governance and risk assessments.
Experience utilizing advanced Microsoft Excel functionalities including macros, VLOOKUPs, pivot tables, and data visualization techniques for analytics and reporting.

Responsibilities

Conduct cybersecurity risk assessments and control effectiveness assessments over critical applications, infrastructure, and enterprise processes.
Perform compliance validations against controls derived from applicable regulations (NYDFS, SOX, MAR) and ensure proper implementation of security controls through evidence analysis.
Design AI Governance model for securing AI assets of New York Life, including inventorying, risk and control assessments, and reporting.
Create knowledge management AI model that consumes company risk and control data and learns from that to answer queries in natural language.
Develop a model capable of answering in-depth questions that typical audience groups (Executives, Asset Owners, Tech/Risk Teams) may ask.
Create protected and controlled landscape for information exchanges.
Streamline and automate cybersecurity residual risk and control effectiveness reporting by designing risk measurement methodologies/processes across various cyber domains.
Develop automated tableau-based dashboards to publish risk and control effectiveness information.
Apply knowledge of AWS and DBMS to implement the underlying AWS database and connections to Tableau.