Data Research Analyst - Banking

Responsibilities 

• Review editorial data requests for feasibility, usability, and scalability.
• Coordinate with research teams to collect banking product and service data.
• Perform analysis on collected data to identify top-quality US banking products, including checking accounts, savings accounts, certificates of deposit, money market accounts, online banks, credit unions, and related banking services.
• Assess banking product attributes such as APYs, fees, minimum balance requirements, account access, customer eligibility, overdraft policies, digital features, and other relevant product criteria.
• Develop and implement processes for quality control, ensuring data accuracy, completeness, and consistency.
• Collaborate with peers to introduce and develop new techniques and processes for efficient data collection.
• Collaborate with the editorial team to ensure deadlines and goals are met.
• Review editorial content resulting from work product for accuracy and completeness.
• Maintain clear documentation of research methodologies, assumptions, data sources, product criteria, and scoring logic.
• Support the continuous improvement of banking data processes, including automation, data validation, and scalable reporting.

About You

• Highly organized, with strong attention to detail and critical thinking abilities.
• Comfortable working in MS Office, with an emphasis on Excel.
• Strong analytical and problem-solving skills.
• Able to interpret banking product information, fees, rates, eligibility criteria, disclosures, and terms and conditions.
• Ability to adapt to a changing environment and prioritize projects accordingly.
• Previous experience in a quality, research, financial services, banking, data, or content role is preferred.
• Comfortable managing your own projects and deliverables.
• Interested in understanding consumer financial products and how data can support accurate, useful editorial recommendations.

Qualifications

• Bachelor’s degree, associate degree, Certificate, or equivalent training and experience in a relevant field such as Business Studies, Economics, Finance, Data Analysis, or a related discipline.
• Proficiency in using Excel for data analysis and manipulation.
• Proficiency in SQL and Python for data manipulation is desirable.
• Experience using BI tools such as Tableau, Power BI, Looker, or similar platforms is highly desirable.
• Experience with financial services data, banking products, consumer finance content, or comparison methodologies is desirable.

Perks

• Day off on the 3rd Friday of every month (one long weekend each month)
• Monthly Wellness Reimbursement Program to promote health well-being
• Monthly Office Commutation Reimbursement Program
• Paid paternity and maternity leaves