Senior Risk Data Analyst

• Bachelor’s or Master’s degree in Data Science, Finance, Accounting, Computer Science, or related field.
  • 5+ years of experience in data analytics, preferably in risk, audit, or financial environments.
• Advanced proficiency in Power BI, SQL, and data visualization techniques.
• Strong understanding of financial principles and audit risk frameworks (e.g., SOX, COSO).
• Experience working with IT teams to manage data pipelines and data lake architecture.
• Ability to craft compelling data stories and present insights to technical and non- technical audiences.
• Excellent communication, stakeholder engagement, and project management skills
• Preferred:
  • Experience with enterprise audit platforms and GRC tools.
  • Familiarity with machine learning techniques for risk forecasting.
  • Knowledge of regulatory environments and enterprise risk management systems.

Physical Requirements and Demands

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Ability to stoop, bend, kneel or crouch.
• Ability to stand, walk and sit.
• Ability to reach with hands and arms
• Visual ability correctable to 20/20.
• Sitting up to 90% of the day.
• Ability to respond verbally in an understandable, professional manner in person and over the telephone.
• Manual dexterity to input data into the computer and the calculator and operate the equipment listed above.
• Ability to lift up to 15 pounds.

Work Environment

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

• Office/ Cubicle workspace.
• Moderate noise level.

#LI-DJ1

• →Design and maintain enterprise-level dashboards that visualize risk metrics, control effectiveness, and audit outcomes using Power BI.
• →Partner with IT teams to ensure seamless data ingestion into the data lake, including defining data requirements and validating data pipelines.
• →Build and maintain semantic models and self-service analytics layers to support audit and risk teams.
• →Develop predictive and descriptive models that support risk profiling and controlled process design.
• →Translate complex datasets into clear, actionable insights and narratives for senior leadership.
• →Ensure data quality, governance, and compliance with internal standards and regulatory requirements.
• →Establish and uphold best practices for responsible AI use, including model transparency, ethical data handling, and bias mitigation.
• →Oversee governance frameworks for the enterprise data warehouse, ensuring data integrity, security, and compliance with regulatory standards.
• →Contribute to the development of analytics frameworks and best practices.
• →Collaborate with finance, audit, compliance, and operations teams to align analytics with business objectives.