Responsibilities

• Strategic Analytics contribution: help drive business outcomes through advanced analytics, including but not limited to:
• Develop the data & measurement roadmap for the Citi Commerce Network (e.g., releases, KPIs, owners)
• Develop and operationalize closed-loop measurement approaches leveraging Citi data and partner signals
• Identify KPIs from online media data sources (Programmatic, Onsite) and combine them into a single measurement view
• Drive standardization of post-campaign reporting, and test-and-learn frameworks
• Develop attribution models and frameworks to establish measurement for Citi Commerce campaigns
• Build and integrate Gen AI capabilities to accelerate measurement and insights generation
• Partner with Finance and Product teams to track actuals versus forecast for business growth and revenue on a granular basis
• Work in a high performing team and develop team members to drive successful outcomes
• Reporting & Insights: Develop and deliver insightful reports, dashboards, and presentations to key stakeholders, translating complex analytical findings into clear, concise, and actionable recommendations.
• Cross-Functional Collaboration: Partner closely with Product Development, Sales, Ad Ops, Audience Analytics, Marketing, and Technology teams to integrate analytical insights into product design, marketing campaigns, and business development initiatives.
• Risk and Controls Governance: Appropriately assess risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients and assets, by driving compliance with applicable laws, rules and regulations, adhering to Policy, applying sound ethical judgment regarding personal behavior, conduct and business practices, and escalating, managing and reporting control issues with transparency, as well as effectively

Requirements

• 6-10 years of progressive experience in data analytics, business intelligence, or quantitative analysis within the financial services, digital media, marketing or retail industry.
• Commerce Media Domain Expertise: Deep understanding of the commerce or retail media landscape, including measurement capabilities, revenue streams, data strategy and commercialization strategy.
• Digital Media and Marketing Expertise: Deep understanding of digital media and marketing ecosystem, including various marketing channels, media buy models, Familiarity with advertising or campaign performance data, ideally across ad servers, web analytics, or DSPs. Knowledge of key digital marketing KPIs (ROAS, Impressions, CTR, CPA etc.)
• Advanced Analytics Skills: Proficiency in statistical analysis, predictive modeling, machine learning techniques, and experimental design (A/B testing). Familiarity with digital marketing principles such as attribution models (MMM, MTA), incrementality testing, AB testing
• Strategic Thinking: Ability to connect analytical insights with business strategy, identifying opportunities and risks.
• Communication Skills: Exceptional verbal and written communication skills, with the ability to articulate complex analytical concepts and present findings clearly and persuasively to both technical and non-technical audiences. Ability to translate advertiser needs into measurement requirements, KPI frameworks, and reporting design
• Problem-Solving: Strong critical thinking and problem-solving abilities, with meticulous attention to detail.
• Technical Proficiency: Data Platforms: Experience with large-scale data platforms and tools (e.g., Snowflake). Experience with first-party data and privacy-safe data environments (e.g., clean rooms, identity resolution). Familiarity with advertising or campaign performance data, ideally across ad servers, web analytics, or DSPs.
• AI/ML skills: Hands-on experience in attribution models and developing Gen AI solutions
• Visualization Tools: Hands-on experience with business intelligence and data visualization tools (e.g., Tableau, Power BI, QlikView).
• Education: Required: Bachelor's degree in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Engineering, or a related discipline. Preferred: Master’s degree or PhD in a quantitative field, Business Analytics, or an MBA with a strong analytical focus.
• Preferred Skills: Experience with programming: proficiency in SQL, Python, or R for data manipulation, statistical analysis, and model development.
• Experience with consumer banking products and customer lifecycle analytics.

Nice to Have

• Master's degree or PhD in a quantitative field, Business Analytics, or an MBA with a strong analytical focus.

Benefits

• medical, dental & vision coverage
• 401(k)
• life, accident, and disability insurance
• wellness programs
• paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays