Marketing Data Science Manager

We are seeking a Marketing Data Science Manager who can bridge the gap between data modeling and business impact. This role will focus on leveraging data science models and analytical frameworks to generate actionable marketing insights, optimize campaign performance, and guide strategic decisions.


Requirements

o Proficiency (10+ years) in analyzing complex data and models, derive and deliver actionable insights to provide data driven marketing strategy to stakeholders. Strong ability to translate model outputs into business insights and marketing recommendations.
o Proficiency (7+ years) in statistical software such as SQL, R, Python, PBI for data wrangling and modeling.
o Familiarity (5+ years) with AWS Sagemaker and Lambda functions. Terraform experience will be preferred.


Experience (required):

o At least 10 years hands on experience in machine learning, marketing analytics, statistical modeling, marketing mix modeling.
o At least 10 years experience with various statistical techniques such as regression analysis, time series analysis, and predictive modeling, optimization etc.
o Familiarity (5+ years) with marketing research methodologies and tools.

Skills

• Proficient in machine learning model and statistical model development, simulation and optimization and deployment in AWS
• Proficient in SQL, Python, R for data integration and modeling projects
• Advanced in AWS Sagemaker, EC2, S3, Terraform, Bitbucket, etc for deployment projects
• Advanced in PBI, Excel, streamlit for analytics and visualization projects
• Experience in Terraform, EC2, MMM, optimizer application will be a big plus

Key Responsibilities:

• Develop and deploy predictive and statistical models to evaluate marketing performance (e.g., attribution, media mix modeling, churn, LTV, segmentation, optimization).
• Partner with marketing, product team to translate modeling results into clear business insights & recommendations that drive growth and ROI and communicate implications to non-technical stakeholders.
• Present findings to senior stakeholders through clear storytelling and visualization.
• Visualize and present analytical results using tools like Power BI, Excel, etc.
• Build and maintain scalable analytics pipelines using Python/R, SQL, and possibly cloud data platforms (Google Cloud Platform, AWS, Azure).
• Partner with marketing operations to operationalize insights (e.g., audience targeting, spend optimization).
• Collaborate with data engineers and analysts to improve data accessibility and accuracy.
• Support ongoing model performance monitoring and iterative improvements.
• Support MMM and app maintenance and development for simulation and optimization and further development. Push changes to production using AWS Sagemaker, EC2, Terraform, Bitbucket, etc.
• Assist with ad-hoc data requests, data exploration and building business knowledge models. Build intelligent dashboards if needed using SQL, PBI.
• Conduct cross-functional collaboration, stakeholder meetings and provide documentations and internal trainings.
• Lead projects, manage timelines, and ensure deliverables meet the business objectives and are delivered on time.
• Perform other duties as assigned or apparent.
• Work with marketing and product teams to design experiments, measure campaign ROI, and inform strategy.