Analyst, Risk Analytics joins the Corporate Information Security Division to design, implement, and evolve a data-driven Global Information Security Risk Analytics platform. This role involves partnering with global information security, IT, and business teams to transform complex datasets into actionable insights that monitor the confidentiality, integrity, and availability of assets. Day-to-day responsibilities include building and maintaining ETL pipelines, developing automation tools for risk measurement, and creating dashboards to track security performance and remediation progress. The position requires proficiency in SQL and Python or R, along with expertise in data modeling, statistics, and visualization. Candidates must possess knowledge of information security concepts like vulnerability management and cloud security. The role addresses the challenge of maturing enterprise-wide security risk intelligence by translating technical findings into compelling stories for both technical and non-technical stakeholders to support senior leadership decision-making.
Build, refine, and maintain ETL pipelines to integrate data from multiple sources while ensuring quality and consistency.
Develop tools, scripts, and automation to streamline data processing, risk measurement, and platform operations.
Create and maintain analytics, metrics, and dashboards to measure security performance and risk exposure.
Analyze large volumes of security and IT data to identify trends, anomalies, and emerging risks.
Translate complex analytical findings into clear, compelling stories for executive and operational stakeholders.
Design and evaluate models used to monitor the confidentiality, integrity, and availability of corporate assets.
Document solutions, workflows, and procedures to ensure consistency and knowledge sharing across the organization.
What we're looking for
Advanced understanding of statistics, data analysis, and data visualization.
Working knowledge of information security and IT concepts such as vulnerability management, cloud security, and risk management.
Ability to analyze large, complex security and IT datasets to identify trends and anomalies.
Experience with data modeling including star/snowflake schema and dimensional modeling.
Proficiency in relational databases (SQL) and programming or scripting languages like Python or R.
Typically 2 years of relevant experience in information security, IT, data analysis, statistics, or a related field.
Bachelor’s degree in Information Security, Computer Science, Statistics, Data Analysis, or a related mathematics/information security field (preferred).
Experience with cybersecurity data sources, version control tools, or data visualization tools like Power BI and Tableau (preferred).
SQL
Tableau
Qlik Sense
Data Modeling
Sigma
ThoughtSpot
Databricks
Data Quality
Reporting
Analytics
Risk Management
Data Engineering
Dimensional Modeling
Data Mesh