Data Scientist
ADT
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- Location
- Irving, TX
- Job type
- Full time
- Posted
- Nov 4
- 2 days ago
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Career path
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About the company
ADT
Consumer services · 10,001+ employees
What you'll do
- 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.
- 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.
- Writing, Talking/Hearing on the phone (Continually=67-100% of workday)
- Remote/Home office (Continually=67-100% of the workday)
- Occasionally, less than 25%
Key skills
data sciencepredictivemarketing analyticsmedia datadigital personalization
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Read the full posting here
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.