AI Data Scientist – Marketing Analytics

Lead the design, development, validation, and deployment of advanced statistical and machine learning models that power Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), audience analytics, and first-party data initiatives, translating complex data into actionable insights that enable data-driven marketing and media investment decisions across the organization.

Responsibilities

• Develop and refine Multi-Touch Attribution (MTA) models to quantify the incremental impact of digital touchpoints across the customer journey.
• Build audience analytics models (segmentation, propensity, lookalike, lifetime value, churn) leveraging first-party data from CRM, CDP, web analytics, and transaction systems.
• Translate model outputs into clear insights, dashboards, and storytelling for marketing and media stakeholders, and influence business decisions.
• Perform exploratory data analysis and feature engineering on marketing datasets from media platforms, ad servers, and CRM/CDP systems; define data requirements with data engineering teams.

Qualifications

1. Bachelor's or master's degree in data science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
2. 5+ years of experience in Data Science, Marketing Analytics, or related fields, with hands-on experience building statistical/ML models.
3. Python (pandas, scikit-learn, statsmodels; PyMC/Stan or open-source MMM libraries such as Robyn/Meridian/PyMC-Marketing preferred) and SQL
4. Statistical modeling: regression, time series, Bayesian methods
5. Machine learning: classification, clustering, forecasting, optimization
6. Cloud platforms: AWS, Azure, or GCP (GCP preferred)
7. Data visualization and BI tools (e.g., Looker, Power BI, Tableau)
8. Familiarity with data warehousing and data modeling concepts