Summary:
The Director of AI ML will be a key strategic and technical leader within ADT’s
Data & AI organization. This individual will be responsible for leading a
high-performing team of data scientists and machine learning engineers to tackle
our most challenging business and technical problems. Leveraging deep expertise
in statistical modeling, machine learning, and scalable AI, the Director will
translate ADT's vast data assets—from smart home IoT telemetry to customer
touchpoints—into actionable business value and predictive products.
The ideal candidate is an inspiring people leader, a hands-on strategic thinker,
and a creative problem-solver. This role requires a strong balance of technical
depth, people management, and the business acumen necessary to collaborate
closely with executive stakeholders while delivering within real-world
constraints
Duties and Responsibilities:
Team Leadership & People Management: Build, lead, and inspire a world-class
team of data scientists; provide active mentorship, career development, and
technical guidance.
Strategic AI/ML Roadmap: Define and execute the data science roadmap,
aligning technical initiatives with ADT's broader business goals, customer
retention strategies, and product development.
End-to-End Delivery: Oversee complex data science projects from conception
through to deployment, ensuring models are scalable, robust, and successfully
integrated into production systems.
Advanced Technical Stewardship: Ensure the team applies rigorous statistical
modeling, machine learning, and data mining techniques to drive measurable
business growth.
Cross-Functional Collaboration: Partner closely with Marketing, Sales,
Operations, and Executive leadership to identify high-impact business
opportunities and design AI-driven solutions.
Data Pipeline & Infrastructure Strategy: Collaborate with data platform and
engineering teams to champion modern MLOps practices, streamline data
pipelines, and improve experimental velocity.
Executive Communication: Translate highly technical and complex data science
concepts, model performance metrics, and strategic recommendations to both
technical and non-technical audiences.
Measurement & Experimentation: Champion experimental design (A/B testing) and
advanced measurement strategies to robustly validate the impact of deployed
data products.
Education: Master’s degree or PhD (preferred) in a quantitative field such as
Computer Science, Statistics, Mathematics, or a related discipline.
Experience: 10+ years of hands-on experience in data science, with at least
3+ years of direct people management experience leading technical teams.
Proven Track Record: Successfully led the development and deployment of
major, production-grade data products or machine learning models that drove
measurable revenue growth, cost savings, or operational efficiency.
Minimum Qualifications:
Technical Depth: Proficient in statistical modeling, machine learning
techniques, and programming languages like Python, with a strong
understanding of cloud data architectures Google Cloud Platform (GCP),
specifically Vertex AI (Pipelines, Feature Store, Model Registry), BigQuery,
and Google Cloud Storage (GCS).
Leadership & Communication: Exceptional leadership, communication, and
collaboration skills, with a proven ability to influence executive
stakeholders and cross-functional partners.
Communication Skills:
Writing, Talking/Hearing on the phone (Continually=67-100% of workday)
Environment Requirements:
Remote/Home office (Continually=67-100% of the workday)