Marketing Business Analyst I

Onsite Role

Job Description:

Role Overview:

• This role supports the Client’s Marketing Mix Modeling (MMM) initiative by assembling, structuring, and validating marketing investment data from multiple sources. You will work with large, messy, and often inconsistent datasets and help transform them into clean, standardized inputs for analytics and modeling.
• This is a hands-on execution role focused on data collection, organization, and quality control. It is ideal for someone early in their career or in a contract capacity who is highly detail-oriented and comfortable working through ambiguity.

Responsibilities:

• Gather marketing spend and activity data from MDF systems, regional teams, and stakeholders
• Clean, normalize, and standardize data across inconsistent formats and definitions
• Break down high-level budget data into more granular components where possible
• Apply defined taxonomy to categorize media spend (channel, tactic, audience, etc.)
• Validate data accuracy and resolve discrepancies with stakeholders
• Maintain structured datasets for MMM and analytics teams
• Support ongoing updates and refresh cycles of marketing data inputs
• Document data sources, assumptions, and transformation logic

Qualifications:

• Experience using LLM models to help cleanse and format data
• 0–3 years of experience in data analysis, marketing analytics, finance, or similar
• Strong attention to detail and comfort working with large datasets
• Proficiency in Excel (required); experience with SQL or BI tools is a plus
• Ability to follow structured processes and apply consistent logic to data
• Comfortable working with incomplete or ambiguous inputs
• Strong organizational skills and willingness to do hands-on data work

Preferred Experience:

• Internship or coursework in analytics, business, or marketing
• Exposure to media or marketing data
• Familiarity with data cleaning or transformation tasks
• · Experience using AI tools to assist with data structuring (nice to have)

Success Metrics:

• Accurate and complete assembly of MMM input datasets, delivered to the vendor, and follow up with the vendor
• Consistent application of taxonomy and data standards
• Reduction in data errors and inconsistencies
• Timely delivery of datasets to analytics teams
• Clear documentation of data sources and transformation