Data Analyst

Job Overview:

The Remediation Analytics team is integral to ensuring fair treatment of card customers by calculating refund amounts when customers are inadvertently negatively impacted by errors or mistakes. This role demands a deep understanding of data analytics, keen attention to detail, and the ability to work closely with business partners to identify and rectify issues across various business areas. The successful candidate will leverage advanced analytical techniques, including segmentation, optimization, and machine learning, to solve complex business problems and ensure accurate restitution for impacted customers.

Key Responsibilities:

• Data Analysis: Work closely with management and cross-functional teams to execute analytical initiatives aimed at solving business problems through advanced data analysis techniques.
• Refund Calculation: Collaborate with Business Risk to develop action plans and calculate refunds accurately, ensuring that every detail is meticulously addressed.
• Advanced Analytics: Lead the development and implementation of analytics initiatives, including customer segmentation, optimization, prescriptive analytics, and machine learning algorithms to drive business solutions.
• Reporting & Dashboards: Create, automate, and prototype reports and dashboards to monitor performance metrics, providing actionable insights and visual displays of quantitative information to various levels of leadership.
• Performance Tracking: Establish and maintain performance tracking systems, identify improvement opportunities, and design and implement tests to enhance and optimize strategies.
• Project Management: Manage multiple priorities simultaneously, ensuring clear communication of business performance and project progress to management and business partners.
• Process Improvement: Consistently follow standard work processes and documentation requirements, recommending improvements to enhance efficiency without compromising quality.
• Continuous Development: Engage in continuous learning to enhance both technical and leadership skills through training and development opportunities.

Qualifications:

• Technical Skills:
  • Strong proficiency in SQL and SAS.
  • Experience in data segmentation, optimization, and the application of advanced analytics and machine learning.
  • Proven ability to develop, automate, and iterate on reports and dashboards.
• Analytical Expertise:
  • Ability to analyze large datasets and translate findings into actionable business recommendations.
  • Expertise in statistical analysis, experimental design, and financial impact analysis.
• Communication Skills:
  • Excellent communication skills, with the ability to present complex findings and recommendations clearly to multiple levels of leadership.
  • Proven ability to collaborate effectively with cross-functional teams and business partners.
• Detail-Oriented:
  • Meticulous attention to detail, ensuring accuracy in all calculations and analytical work.
• Project Management:
  • Strong project management skills, with the ability to manage multiple priorities and deliver on time. 

Preferred Experience:

• Experience in a financial services or credit card environment.
• Experience with customer remediation or restitution processes.
• Familiarity with business risk assessment and mitigation strategies.

Education:

• Bachelor’s degree in Data Science, Statistics, Mathematics, Finance, or a related field. Advanced degrees are a plus.