Senior Manager, Applied Science

About the role

The owns the strategic vision and execution roadmap for the Machine Learning team, defining the technical direction that powers autonomous advertising. You will architect intelligent systems that transform advertising workflows by leveraging advanced machine learning to solve high-stakes business problems with measurable impact. This role requires you to establish and enforce world-class engineering practices that ensure models are robust, scalable, and maintainable over the long term. You will act as a technical thought partner to executive leadership, shaping investment priorities and innovation bets for the data and AI initiatives. Driving the full lifecycle ownership of machine learning models - from exploratory research and prototyping through production deployment, monitoring, and iterative optimization - is a core responsibility. You will foster a culture of scientific rigor and curiosity within your team, encouraging experimentation while maintaining a disciplined approach to delivery and quality. Success in this position is defined by your ability to translate ambiguous business challenges into concrete technical strategies that unlock new value across the advertising ecosystem.

Key facts

What you'll do

Define and lead the technical strategy for the Machine Learning Engineering team, setting the vision for model development and deployment in the advertising domain.

Architect scalable machine learning pipelines that process high-volume data streams to support real-time decision-making in digital campaigns.

Design and implement advanced supervised learning and causal inference models to forecast content demand and quantify incremental lift in media exposure.

Develop frameworks for precise personalization and targeting that respect privacy constraints and align with evolving regulatory standards.

Partner closely with Product, Finance, and Content teams to deconstruct complex business problems and translate objectives into testable hypotheses and technical specifications.

Establish rigorous experimentation methodologies and evaluation metrics to validate model performance and drive evidence-based product improvements.

Mentor engineers and data scientists, elevating the team's ability to deliver production-grade solutions with clean architecture and maintainable code.

Champion research initiatives that explore novel statistical techniques and emerging methodologies to maintain a competitive edge in autonomous advertising.

Collaborate with cross-functional stakeholders to identify opportunities for automation, efficiency gains, and data-driven optimizations across the media value chain.

Own the deployment and monitoring of models in production, ensuring reliability, observability, and alignment with business KPIs over time.

Champion data quality and infrastructure improvements that enable faster iteration cycles and more reliable insights for decision-makers.

Facilitate knowledge transfer across teams by documenting methodologies, model behaviors, and best practices for machine learning operations.

Lead scoping and prioritization exercises to balance innovation efforts with immediate business needs and technical debt reduction.

Act as the technical authority on machine learning for the advertising platform, representing the function in strategic planning and roadmap discussions.

Drive the adoption of MLOps best practices to streamline model updates, reduce deployment friction, and enhance collaboration between data science and engineering.

Requirements

You hold a Bachelor's degree in Computer Science, Engineering, or a closely related quantitative field.

A Master's degree is highly desirable and preferred for deeper theoretical understanding and advanced problem-solving.

You bring a minimum of seven years of professional experience in machine learning or related technical fields.

This includes at least three years of hands-on experience leading and scaling high-performing engineering teams.

You have a proven track record of delivering complex machine learning solutions at scale in production environments.

Your background demonstrates strong operational discipline, including monitoring, logging, and incident response for data-driven systems.

You possess exceptional analytical and problem-solving abilities, capable of navigating poorly defined challenges that have not been previously addressed.

You show a history of successful collaboration across technical, business, and executive functions within matrixed organizations.

You are comfortable making decisions in environments with ambiguity while relying on data, experimentation, and sound judgment.

You communicate effectively with both technical and non-technical stakeholders, translating complex concepts into actionable recommendations.

You have experience working with large datasets and distributed computing frameworks relevant to advertising-scale workloads.

You are proficient in modern machine learning frameworks and programming languages commonly used in production systems.

You understand software engineering best practices, including version control, testing, and continuous integration within a DevOps culture.

You have a strong sense of ownership and accountability for end-to-end product outcomes and team performance.

Nice to have

A PhD in Machine Learning, Computer Science, or a closely related field provides a distinct advantage for this role.

Direct experience in the digital advertising or Ad Tech industry, with exposure to demand-side platforms and marketplace dynamics.

A history of contributing to reputable academic or industry conferences through publications, talks, or active participation.

Experience with privacy-preserving machine learning techniques and compliant data strategies in advertising contexts.

Familiarity with CTV environments, connected TV ecosystems, and the unique measurement challenges they introduce.

Practical notes

This is a full-time position based in the United States.

Candidates must be authorized to work in the United States without sponsorship for this role.

Relocation is not sponsored by Viant Technology for this position.

The compensation details provided represent Viant's good-faith estimate and are subject to adjustment based on candidate qualifications and final role determination.