Staff Data Scientist

MNTN is looking for a Staff Data Scientist to lead the development of advanced algorithms and modeling approaches that drive performance and targeting precision across our entire advertising platform. This is a high-impact, senior-level role responsible for foundational work that will affect every advertiser we serve.

You’ll focus on two core mandates:

• Expanding Converter Reach: Growing the number of households we can confidently predict are likely to convert for any given brand.
• Improving Precision: Increasing the accuracy of our predictions about which households will convert, ensuring that spend is used efficiently and results are maximized.

You’ll work with vast, diverse datasets—from consumer site behavior and purchase history to ad exposure and response—and partner closely with engineering, product, and analytics teams to deploy solutions that scale.

What You’ll Do: 

• Design and implement advanced algorithms to identify high-likelihood converters at the household level across multiple verticals and audience segments, driving measurable improvements in campaign outcomes.
• Build, productionize, and maintain predictive models that directly support targeting, bidding, and optimization systems at scale.
• Take ownership of end-to-end model development workflows, including data exploration, feature engineering, validation, deployment, and ongoing performance monitoring.
• Develop and refine measurement methodologies to quantify model precision and campaign impact, working with stakeholders to ensure consistent evaluation standards.
• Collaborate closely with product managers, engineers, and fellow scientists to influence system design and ensure scientific solutions are robust, scalable, and aligned with business goals.
• Provide technical guidance on modeling approaches and data strategies within the Targeting team, contributing to peer reviews and team-wide quality standards.
• Stay informed on cutting-edge developments in machine learning and targeting science, proactively applying relevant techniques to elevate model performance and efficiency.

What You’ll Bring: 

• 8+ years of experience in data science, with a proven track record of delivering ML/optimization solutions in a production environment.
• Deep expertise in predictive modeling, uplift modeling, targeting optimization, and/or large-scale personalization systems.
• Strong coding skills in Python, SQL, and experience with ML/analytics libraries (scikit-learn, XGBoost, Spark, etc).
• Fluency in causal inference methods, probabilistic modeling, and experimentation frameworks.
• Familiarity with advertising data ecosystems: user behavior data, conversion tracking, pixel and event data, identity graphs, etc.
• Exceptional communication and cross-functional collaboration skills—able to influence both technical and non-technical stakeholders.
• Preferred: Experience with graph databases.