The marketing agency is looking to transform data into actionable insights to guide decision-making and enhance the effectiveness of marketing initiatives for their clients. They also aim to build and advance their proprietary AI-powered tools, specifically their AI-Powered Business Intelligence platform, by embedding advanced data science and machine learning capabilities.
Requirements
- Strong proficiency with SQL and relational databases.
- Advanced skills in Python or R for statistical analysis, modeling, and machine learning.
- Experience with statistical learning methods: regression, clustering, PCA, decision trees, Bayesian inference, MCMC.
- Hands-on experience in marketing analytics solutions: Customer Segmentation, MMM, MTA, churn/retention modeling.
- Familiarity with media channels (TV, radio, print, search, display, social, email, ecommerce) and their measurement frameworks.
- Knowledge of martech/adtech tools: Ad Servers, DSPs, DMPs, CRMs, syndicated research sources.
- Familiarity with data visualization platforms (Tableau, Power BI, Looker).
Responsibilities
- Define and size total addressable markets (TAM) for client initiatives.
- Segment audiences into meaningful personas using behavioral, demographic, psychographic, and cultural data.
- Build, implement, and maintain marketing mix models (MMM), multi-touch attribution (MTA) frameworks, and media performance dashboards.
- Recommend A/B and multivariate testing to optimize creative, targeting, and media allocation.
- Develop and apply statistical and machine learning models (e.g., regression, clustering, PCA, decision trees, ARIMA forecasting).
- Forecast campaign outcomes, customer acquisition costs, and lifetime value.
- Collaborate closely with the development team to embed data science and AI capabilities into our proprietary platforms, especially our AI-Powered Business Intelligence tool.
Other
- Bachelor’s degree in a STEM field (Statistics, Computer Science, Engineering, Economics, etc.) or equivalent experience.
- Strong communication skills—able to present work clearly to internal teams and clients.
- Experience with psycholinguistic or cognitive-based analysis of customer behavior.
- Background in consumer psychology, behavioral economics, or cultural analytics.
- Experience with cloud platforms (AWS, GCP, Azure) for large-scale data processing.
