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Summary:

The Data Scientist, Marketing Analytics serves as a core analytical authority on ADT's marketing efforts, translating complex customer, campaign, and media data into high-value, predictive, and actionable insights. This role bridges the gap between advanced data science and strategic marketing operations, working with stakeholders to solve critical business problems like predicting high-value customer acquisitions, optimizing media spend, and supporting our company's growth, customer lifetime value (LTV), and digital personalization objectives. 

The ideal candidate combines strong technical capabilities in machine learning, statistical modeling, and data engineering with an understanding of consumer behavior, marketing technology (MarTech), and executive storytelling. They will work alongside the Marketing Analytics Leader, data analysts, data engineers, and channel managers to build scalable, evidence-based solutions that directly influence ADT's customer acquisition and retention strategies. 

Duties and Responsibilities:

• Predictive Growth Modeling: Apply advanced statistical methods, machine learning (e.g., classification, survival analysis), and clustering to predict customer lifetime value (LTV), model acquisition propensity, and identify customer churn risk. 

• Attribution & Mix Modeling: Support the development of Marketing Mix Modeling (MMM) and multi-touch attribution (MTA) frameworks to help business leaders understand and act on marketing efficiency issues. 

• Campaign Experimentation: Design and execute evidence-based research and scientific hypothesis testing (A/B and multivariate testing) around digital marketing campaigns, creative assets, and landing page personalization. 

• Executive Data Storytelling: Translate highly complex statistical findings into clear, beautiful, and intuitive visualizations and compelling narratives that drive strategy, action, and decision-making at executive levels. 

• Data Engineering & Pipelines: Collaborate with data platform and engineering teams to design, implement, and maintain robust data pipelines that integrate ad-platform APIs, web analytics, and offline sales data into a continuous, single-source-of-truth. 

• Privacy & Compliance: Implement and champion rigorous data privacy standards and ethical data collection practices, navigating how to effectively target and optimize campaigns while respecting consumer privacy regulations (e.g., CCPA/CPRA, cookie changes). 

• Cross-Functional Collaboration: Partner directly with Brand, Digital Media, Demand Gen, and Product Marketing teams to frame vague marketing challenges into structured, measurable data science initiatives. 

• Continuous Improvement: Stay current on evolving marketing technology trends, MLOps best practices, and innovative data sources to elevate ADT's analytical maturity from descriptive reporting to prescriptive action.

• Customer Segmentation: Experience creating and defining customer personas and segmentation to deliver personalized experiences throughout the customer lifecycle. 

Minimum Qualifications:

• Education: Bachelor's degree (or equivalent experience) in Analytics, Computer Science, Statistics, Mathematics, Economics, or a related highly quantitative field. (Master's degree preferred). 

• Experience: 3+ years of directly applicable experience in data science, predictive modeling, and building end-to-end data pipelines within a marketing or customer acquisition context. 

• Technical Proficiency:

  • Advanced proficiency in (Python with deep experience in data modeling packages. 

  • Advanced SQL skills and experience manipulating high-dimensional consumer datasets.

  • Proficiency using Vertex AI/Colab notebooks.

• Domain Knowledge: Solid understanding of digital marketing channels (Paid Search, Paid Social, Programmatic), web analytics platforms (e.g., Google Analytics, Adobe Analytics), and MarTech/AdTech ecosystems. 

• Ambiguity Management: Proven ability to navigate dynamic, fast-paced, and entrepreneurial environments with ambiguous or evolving project requirements.

• Familiarity with Customer Data Platforms (CDP) in supporting no code/low code Marketer driven target audiences.

Communication Skills:

• Writing, Talking/Hearing on the phone (Continually=67-100% of workday)

Environment Requirements: 

• Remote/Home office (Continually=67-100% of the workday)

Travel:

• Occasionally, less than 25%