Commerce & Media Analytics Analyst

The Spec Analytics Intmd Analyst is a developing professional role. Deals with most problems independently and has some latitude to solve complex problems. Integrates in-depth specialty area knowledge with a solid understanding of industry standards and practices. Good understanding of how the team and area integrate with others in accomplishing the objectives of the sub function/ job family. Applies analytical thinking and knowledge of data analysis tools and methodologies. Requires attention to detail when making judgments and recommendations based on the analysis of factual information. Typically deals with variable issues with potentially broader business impact. Applies professional judgment when interpreting data and results. Breaks down information in a systematic and communicable manner. Developed communication and diplomacy skills are required in order to exchange potentially complex/sensitive information. Moderate but direct impact through close contact with the businesses' core activities. Quality and timeliness of service provided will affect the effectiveness of own team and other closely related teams.

 

Citi is evolving its current commerce offerings and branching into new avenues of growth. By combining Citi’s scale, trusted customer relationships, and real purchase insights, the business delivers advertising that is relevant to customers and drives measurable, incremental impact for advertisers. This role will leverage data-driven insights to optimize targeting and personalization, enhance customer engagement, and identify new growth opportunities. The successful candidate will be working hands-on as a part of a team or function focused on in-depth analysis of 1st, 2nd and 3rd party data and underlying customer behaviors as well as advertiser preferences to develop audiences, hands-on as a part of a team or function focused on in-depth analysis of campaign performance for commerce media ads and offers and their impact on underlying customer behaviors and development of attribution models and frameworks to deliver detailed insights to advertisers. This position requires a deep understanding of the commerce media business, digital ecosystem, strong analytical capabilities.

 

Qualifications: Preferred - Master's degree in a quantitative field, Business Analytics, or an MBA with a strong analytical focus

Experience : 4 to 7 years (preferably 5 years+)

Relevant experience : Audience related Analytics for 3 years+

 

Expertise:

• 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. Proficiency in statistical analysis, predictive modeling, machine learning techniques, and experimental design (A/B testing). Experience building audience segments using 1P data, behavioral signals, and transaction data

 

Technical Proficiency:

• Data Platforms:
  •  Experience with large-scale data platforms and tools (e.g., Snowflake).
  • Experience working 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).

 

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.