Data Scientist

Responsibilities

The Data Scientist will translate complex marketing data into predictive insights to optimize customer acquisition, retention, and media spend. They will design experiments, build robust data pipelines, and collaborate with cross-functional teams to drive evidence-based marketing strategies.

Requirements

Candidates must have at least 3 years of experience in data science and predictive modeling within a marketing context. A bachelor's degree in a quantitative field is required, along with advanced proficiency in Python and SQL.

Skills

• Python
• SQL
• Machine Learning
• Statistical Modeling
• Data Engineering
• Marketing Analytics
• Predictive Modeling
• Customer Lifetime Value
• Marketing Mix Modeling
• Attribution Modeling
• A/B Testing
• Data Visualization
• Vertex AI
• Customer Data Platforms
• Data Privacy
• Executive Storytelling

About this role

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%

About ADT

Security and Investigations · 501-1,000 employees · headquartered in Boca Raton, FL