Data Scientist

Irving, TX, United States

Live, first seen by us 77 days ago

Pay: Pay not listedSimilar roles state $118K–$195K
Work setting: Not stated
Employment: Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

What you’ll work on

Full posting

Build models for customer lifetime value, acquisition propensity and churn risk
Support marketing mix and multi-touch attribution frameworks
Design and run A/B and multivariate tests on campaigns and landing pages
Turn complex findings into executive-level visualizations and narratives
Help maintain data pipelines that integrate ad-platform, web and offline sales data

From the employer’s posting

predict customer lifetime value (LTV), model acquisition propensity, and identify customer churn risk

Support the development of Marketing Mix Modeling (MMM) and multi-touch attribution (MTA) frameworks

Design and execute evidence-based research and scientific hypothesis testing (A/B and multivariate testing)

Translate highly complex statistical findings into clear, beautiful, and intuitive visualizations and compelling narratives

design, implement, and maintain robust data pipelines that integrate ad-platform APIs, web analytics, and offline sales data

What you’ll bring

All qualifications

Core experience

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.
Proficiency using Vertex AI/Colab notebooks.
Familiarity with Customer Data Platforms (CDP) in supporting no code/low code Marketer driven target audiences.

Qualification wording

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.

Proficiency using Vertex AI/Colab notebooks.

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

Education & alternatives

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.

Apply at Adt

Posting record

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Status in our records: Live
First seen by us: Aug 26, 202677 days ago
Recorded sightings: 15
Last seen by us: Nov 12, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$195K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,828 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 77

Up longer than most. Similar jobs usually come down between day 8 and day 59.

At Adt, jobs usually come down by about day 40.

From 11,601 similar postings that came down, and 9 of Adt’s. Coming down is not always a hire.

Adt is hiring

2 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Takes jobs down at a usual pace

Hiring record

See how this role fits your experience

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Python
SQL

Where the posting names them

- Technical Proficiency: - Advanced proficiency in (Python with deep experience in data modeling packages. - Advanced SQL skills and experience manipulating high-dimensional consumer datasets.

- 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.

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About Adt

People: About 12,200 in 2025, down 5% from the year before.Annual report (SEC Form 10-K)
Company: Listed as ADT.

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.

August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025: $120,230
Expected change, 2025 to 2035: 34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

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%

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