Data Analyst

Responsibilities

• Analyze customer, marketing, campaign, product, and channel data to identify trends, opportunities, and business insights.
• Develop and maintain marketing dashboards, reports, scorecards, and key performance indicators (KPIs).
• Measure and evaluate the effectiveness and ROI of marketing campaigns across digital, email, direct, social, and other channels.
• Analyze customer acquisition, engagement, conversion, retention, and cross-sell opportunities.
• Develop customer segments and profiles to support targeted marketing campaigns and customer lifecycle strategies.
• Partner with Marketing and business leaders to define analytical requirements and translate business questions into data-driven solutions.
• Use SQL and other analytical tools to extract, manipulate, validate, and analyze large and complex datasets.
• Identify trends, patterns, and opportunities within customer and marketing data and translate findings into actionable recommendations.
• Support campaign targeting, testing, measurement, and optimization initiatives, including A/B testing.
• Develop dashboards and visualizations that provide Marketing leadership with visibility into campaign and business performance.

Requirements

• Bachelor’s degree in Marketing, Business, Finance, Economics, Statistics, Data Analytics, Computer Science, or a related field.
• Minimum of 3 years of professional experience in marketing analytics, data analytics, business intelligence, customer analytics, or a related analytical field.
• Experience within banking, financial services, fintech, payments, or another regulated industry.
• Experience analyzing marketing, customer, campaign, digital, or financial data.
• Strong SQL skills and experience querying and analyzing large datasets.
• Strong proficiency with Microsoft Excel, including pivot tables, lookups, data manipulation, and analysis.
• Experience with data visualization and business intelligence tools such as Tableau, Power BI, or similar platforms.
• Knowledge of Python, R, SAS, or other statistical/analytical programming languages.
• Experience with A/B testing, predictive analytics, or statistical modeling.
• Demonstrated ability to translate complex data into actionable business insights.