Marketing Data Scientist Manager

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Marketing Data Science Manager (Virtual Role)

Schedule: Full-time, 40 hours/week

Contract Position

About The Organization

Join a pioneering leader in online education that’s dedicated to empowering working adults and lifelong learners through accessible, high-quality programs. This organization is redefining how data and technology drive marketing strategy, student engagement, and business growth. You’ll be part of a collaborative environment that values innovation, integrity, and impact — where data-driven insights help transform the educational journey for thousands of learners nationwide.

About The Role

We’re seeking a Marketing Data Science Manager to bridge the gap between advanced analytics and real-world business impact. In this role, you’ll design and implement data science models and analytical frameworks to uncover actionable insights, optimize marketing performance, and inform strategic decisions across multiple channels.

The ideal candidate combines deep technical expertise with strategic thinking and strong communication skills — transforming complex data into compelling narratives that guide decision-making and drive measurable results.

<>Key Responsibilities</>

• Develop and deploy predictive and statistical models to evaluate and enhance marketing performance (e.g., attribution, media mix modeling, churn, LTV, segmentation, optimization).
• Partner with marketing and product teams to translate analytical results into clear, actionable insights that fuel growth and ROI.
• Present findings through compelling data storytelling and visualization using Power BI, Excel, or similar tools.
• Build and maintain scalable analytics pipelines using Python/R, SQL, and cloud platforms (AWS, Azure, or Google Cloud Platform).
• Collaborate with data engineering and marketing operations teams to operationalize insights for targeting and spend optimization.
• Lead cross-functional projects, manage timelines, and ensure analytics deliverables meet business objectives.
• Support model maintenance, performance monitoring, and continuous improvement.
• Conduct ad-hoc analyses, develop dashboards, and contribute to marketing experimentation and A/B testing initiatives.

<>Qualifications</>

Education:

Bachelor’s or Master’s degree in Statistics, Economics, Operations Research, Computer Science, Industrial Engineering, Mathematics, or a related field.

Experience & Technical Skills:

• 10+ years of experience in machine learning, marketing analytics, and statistical modeling.
• Proven ability to interpret and communicate model results into marketing insights and strategic recommendations.
• Advanced proficiency in SQL, Python, R, and visualization tools (Power BI, Excel, Streamlit).
• Strong experience with AWS services such as SageMaker, EC2, S3, and Lambda (Terraform experience preferred).
• Familiarity with marketing research methods, experimentation, and advertising platforms (Google Ads, DV360, etc.).
• Understanding of marketing mix modeling, attribution modeling, and optimization techniques.

Preferred Experience:

• AI-driven marketing or multi-touch attribution modeling.
• Experience deploying and maintaining models in cloud environments.
• Proficiency in Terraform, Bitbucket, and automation for analytics workflows.

<>Core Competencies</>

• Analytical Rigor: Ability to manage complex data, derive insights, and recommend data-driven marketing strategies.
• Business Acumen: Deep understanding of marketing channels, campaign effectiveness, and strategic alignment with organizational goals.
• Communication: Clear, concise, and compelling storytelling that bridges the technical and business communities.
• Collaboration: Skilled at cross-functional partnership with media, creative, finance, and product teams.

<>What You’ll Gain</>

• The opportunity to help shape a growing marketing analytics function at a mission-driven educational organization.
• Direct influence on marketing strategy, campaign performance, and customer growth initiatives.
• Exposure to advanced data science, AI, and experimentation techniques in a data-first culture.
• A potential pathway to full-time employment with meaningful career growth opportunities.