Senior Principal Data Scientist (AI)

TL;DR

Senior Principal Data Scientist (AI): Designing and building advanced machine learning models and reinforcement learning systems for ad serving and advertiser outcome optimization with an accent on petabyte-scale data, low-latency prediction, and causal inference. Focus on transforming platforms from impression-based to outcome-driven intelligence, solving complex multi-touch attribution challenges, and leading technical science strategy.

Location: Remote/Hybrid within the United States

Salary: $160,965 - $349,885/yr

Company

An industry-leading ad tech solution providing trusted data and machine learning at a global scale across major digital brands.

What you will do

• Define the machine learning and data science strategy for closed-loop measurement and advertiser outcome optimization.
• Design and deploy production-grade ML models for conversion, click-through rate, and engagement scoring at petabyte scale.
• Develop reinforcement learning and contextual bandit systems for real-time bid optimization and dynamic floor pricing.
• Lead experimentation frameworks, A/B testing strategies, and causal inference methodologies to protect revenue and enable rapid iteration.
• Mentor data scientists and ML engineers while collaborating with product and sales stakeholders to define success metrics.
• Establish automated ML pipelines for training, drift detection, and feature serving infrastructure.

Requirements

• Ph.D. in Computer Science, Machine Learning, or Statistics with 8+ years of experience (or M.S. with 12+ years).
• Proven record of shipping production ML systems that drive measurable business impact at scale.
• Expertise in reinforcement learning and contextual bandit algorithms applied to real-world problems.
• Proficiency in Python, SQL, and distributed computing frameworks like Spark or Beam.
• Experience with ML frameworks such as TensorFlow, PyTorch, or JAX within cloud environments (Vertex AI/SageMaker).
• Strong ability to communicate complex technical strategy to senior leadership.

Nice to have

• Background in ad tech, programmatic advertising, or computational advertising.
• Knowledge of offline policy evaluation, counterfactual reasoning, or multi-objective optimization.
• Experience with NLP, transformer models, or large language models for recommendation systems.
• Publications in top ML/AI venues like NeurIPS, KDD, or RecSys.

Culture & Benefits

• Comprehensive benefits including high-quality healthcare and 401(k) plans.
• Flexible hybrid work policy with support for remote work.
• Incentive compensation opportunities including discretionary annual bonuses.
• Access to 11 employee resource groups (ERGs) fostering an inclusive and diverse culture.
• Education stipends and professional development support.