Marketing Data Science Manager Position

:JD

We are hiring a Marketing Data Science Manager to leverage analytical frameworks and predictive modeling for actionable marketing insights and campaign optimization.

Key Requirements

• Education: Bachelor’s or Master’s in Statistics, Economics, Marketing Analytics, Computer Science, or related fields.
• Experience:
• 10+ years in machine learning, marketing analytics, statistical modelling, and marketing mix modeling.
• 10+ years applying regression analysis, time series analysis, predictive modeling, and optimization.
• 7+ years with statistical software: SQL, R, Python, Power BI.
• 5+ years with AWS Sage maker, Lambda, marketing research tools/methodologies.
• Terraform experience preferred.

Skills:

• Proven ability to translate data/model outputs into actionable business and marketing strategies.
• Strong problem-solving and attention to detail.
• Track record of clear, concise communication with technical and non-technical stakeholders.
• Collaborative mindset with cross-functional teams (media, creative, product, finance).
• Good to have:
• Experience in AI/multi-touch attribution models, ad platforms (Google Ads, DV360), A/B testing, and experimentation frameworks.

Advanced Skills

• Model development, deployment, and optimization in AWS (Sagemaker, EC2, S3, Terraform, Bitbucket).
• Data integration and modeling using SQL, Python, R.
• Analytics/visualization with Power BI, Excel, streamlit.
• MMM, optimizer applications; building scalable analytics pipelines (Python/R, SQL, cloud platforms).

Key Responsibilities

• Develop and deploy predictive/statistical models to evaluate marketing performance (attribution, MMM, churn, LTV, segmentation, optimization).
• Translate modeling results into business recommendations and present findings using storytelling and visualization tools.
• Build and maintain analytics pipelines; operationalize insights for audience targeting and spend optimization.
• Partner with marketing operations, data engineering, and analysts to improve data accessibility and accuracy.
• Monitor model performance, improve simulation/optimization apps, and push updates to production.
• Handle ad-hoc data requests, exploration, and intelligent dashboard creation.
• Collaborate cross-functionally, provide documentation and internal trainings, and manage project timelines and deliverables.
• Support experiment design, ROI measurement, and strategy development with marketing/product teams.

Benefits & Opportunities

• Direct impact on shaping the marketing data science/insights function.
• Influence marketing strategy and customer growth.
• Exposure to advanced analytics and experimentation in a data-driven organization.
• Career growth and pathway to possible full-time employment.