Senior Associate - Data Risk Analyst

New York Life•New York, NY

4d•$124,000 - $177,000•Hybrid

About The Position

The Data Risk Analyst plays a key role in advancing New York Life’s enterprise data risk management program by developing and maintaining the frameworks, metrics, reporting, and processes used to identify, measure, monitor, and mitigate data risk. As part of the Data Governance & Data Risk Management function, this role will partner with data owners, stewards, technology teams, Enterprise Risk Management, Compliance, and other stakeholders to strengthen data risk practices across the organization. The Data Risk Analyst will help develop and evolve New York Life’s data risk taxonomy, operationalize Key Risk Indicator (KRI) and Key Performance Indicator (KPI) frameworks, maintain the data risk register, produce risk reporting and dashboards, and support the remediation of identified risks. The role will also contribute to data protection and governance initiatives across cloud-based data environments and help embed consistent data risk practices into day-to-day operations.

Requirements

5–8 years of professional experience in data governance, data risk management, enterprise risk management, or a related field, with demonstrated experience developing or maintaining structured data risk taxonomies and aligning data risks to broader enterprise risk frameworks.
Hands-on experience designing and operationalizing KRI/KPI frameworks, including metric definition, threshold setting, ownership, reporting cycles, risk monitoring, and remediation tracking.
Strong analytical and reporting capabilities, including experience using tools such as SQL, Tableau, or equivalent technologies to translate data and risk metrics into clear reporting, dashboards, visualizations, and risk narratives for technical and non-technical audiences.
Working knowledge of data governance and risk concepts, including data quality, metadata management, data lineage, data classification, data protection, and risk tracking, along with experience using tools such as Jira, Confluence, SharePoint, or GRC platforms.
Strong communication, problem-solving, and stakeholder management skills, with the ability to collaborate across data, technology, business, risk, compliance, and governance teams and communicate complex risk topics effectively to senior stakeholders.
Bachelor’s degree in Information Systems, Computer Science, Data Science, Business, or a related field, or equivalent experience.

Nice To Haves

Experience within financial services, insurance, or another regulated industry and familiarity with industry frameworks such as DAMA-DMBOK, DCAM, FAIR, or the NIST Cybersecurity Framework.
Familiarity with data catalog, data quality, or observability platforms such as Atlan, Anomalo, Collibra, or equivalent technologies, as well as cloud data environments such as AWS and GCP.
Exposure to data security and privacy risk concepts, including PII/PHI, data classification, Data Security Posture Management (DSPM), and data protection approaches for structured and unstructured data.
Understanding of AI and algorithmic data risk, including model data risk and Generative AI or LLM governance considerations, and experience working within Agile delivery environments.

Responsibilities

Develop and operationalize enterprise data risk frameworks by maintaining the data risk taxonomy, defining risk categories and descriptions, and partnering with Enterprise Risk Management, Compliance, Legal, technology, and data stakeholders to align data risk practices with broader enterprise risk frameworks and evolving business and regulatory needs.
Define, measure, and communicate data risk by establishing KRIs and KPIs, thresholds, escalation triggers, ownership, and reporting methodologies; maintain the data risk register and create dashboards and actionable reporting that provide governance and executive stakeholders with visibility into risk posture, trends, and emerging issues.
Drive risk mitigation and remediation by tracking findings, exceptions, and corrective actions; partnering with risk owners to address aging or recurring issues; supporting risk acceptance and escalation processes; and contributing to playbooks and standard operating procedures for common data risk scenarios.
Advance data protection and governance practices across enterprise data environments, collaborating with data owners, stewards, product managers, risk and compliance partners, and engineering teams to support data protection, classification, quality, lineage, metadata, measurement, and monitoring capabilities across cloud data platforms.
Build data risk awareness and adoption by partnering across business and technology teams, supporting governance committees and risk forums, and leading enablement activities such as roadshows, training, and onboarding sessions. Contribute to Agile delivery by helping manage priorities, requirements, stakeholder feedback, and the delivery of data risk capabilities.