Sr. Fraud Business Intelligence Analyst (SAS, SQL, Python, Tableau)

$86,840 - $139,360/Yr

TD Bank - Greenville, SC

Full-time - Mid Level

Remote - Greenville, SC

Credit Intermediation and Related Activities

About the position

The Sr. Fraud Business Intelligence Analyst, also known at TD Bank as The Fraud Business Strategy Specialist, plays a crucial role in the US Fraud division by creating reports and dashboards for various partners. This position requires proficiency in tools such as SAS, Tableau, SQL, and Python to support different product lines. The analyst will be responsible for developing ETL processes, dashboards, and reporting using Tableau, as well as writing high-quality SQL and SAS code to retrieve and analyze data from various database tables. Additionally, the analyst will handle ad-hoc requests and projects, providing ongoing reporting and thought leadership in business analysis as needed. This role is primarily remote, but candidates must attend in-person meetings once a quarter at designated locations, including New Jersey, Maine, South Carolina, North Carolina, Maryland, Massachusetts, Florida, and Connecticut. The working hours are Monday to Friday, from 8:00 AM to 5:00 PM. Candidates must be authorized to work in the United States without employer sponsorship. The position involves oversight of fraud attacks and trends, partnering with senior leadership to implement countermeasures aligned with strategic goals. The analyst will participate in forecasting exercises related to fraud loss and operational capacity, implement procedure changes, and adhere to Change Management protocols. They will leverage business-level reporting to identify fraud trends and provide insights based on their area of oversight, supporting project development and risk identification while ensuring alignment with fraud policies and processes.

Responsibilities

• Create reports and dashboards for various partners across the US Fraud division.
• Develop ETL processes and dashboards using Tableau.
• Write high-quality SQL and SAS code to retrieve and analyze data from different database tables.
• Develop queries and visualizations for ad-hoc requests and projects.
• Lead the design, development, and management of analytical tools and reporting.
• Provide thought leadership and business analysis support as needed.
• Oversee fraud attacks and trends impacting identified areas.
• Partner with senior leadership to implement countermeasures in accordance with strategic goals.
• Participate in quarterly and annual fraud loss and operational capacity forecasting exercises.
• Implement procedure and project changes while adhering to Change Management protocols.
• Leverage business-level reporting to identify fraud trends and provide insights.
• Support project development and provide risk identification for business insight.
• Ensure fraud policy/process alignment and implementation for both fraud and supported business lines.
• Provide monthly business partner loss and operational performance updates.

Requirements

• Bachelor's degree in a related discipline.
• 3-5 years of work experience in a related capacity.
• Experience with SAS, SQL, Tableau, and Python preferred.
• Experience in fraud management preferred.
• Proficient with Microsoft Office applications; Advanced Excel preferred.
• Strong communication skills and ability to develop effective relationships with business partners.
• Skilled in managing budgets, P&L, and resource allocation.
• Ability to handle confidential information with discretion.

Nice-to-haves

• Undergraduate level education in Business, Computer Science, Mathematics, Economics, or other quantitative disciplines preferred.
• Deep understanding and hands-on experience with Tableau and Power BI preferred.
• Experience with relational databases and ETL processes using SQL or SAS preferred.
• Expert knowledge of various data sources, tools, and technologies used in preparing and summarizing reports preferred.
• Strong analytical and problem-solving skills to interpret data and draw conclusions preferred.
• Demonstrated time management and organizational skills with the ability to prioritize multiple initiatives preferred.
• Experience within a Data Warehousing/Business Intelligence environment preferred.