Lead Data Scientist / Manager -Must Have AWS, Python, Machine learning, Marketing Analytics, statistical techniques - Full Remote (Phoenix)

Role : Data Science Developer / Manager

Location : Remote

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 (GCP, 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.