Lead the full Machine Learning (ML) life-cycle from data extraction and feature engineering to model training, validation, and deployment for critical marketing capabilities. Design and build ML models that solve ambiguous business problems and optimize the full customer life-cycle and demand funnel.

Design scalable data science applications using Google’s LLM models to unlock insights from structured and unstructured data, build intelligent marketing agents, and automate decision-making processes within the Business-to-Business (B2B) funnel.

Define coding standards and engineering best practices for the team; mentor other data scientists on writing production-quality code and designing scalable architectures.

Partner with engineering and cross-functional data science teams to integrate model outputs directly into our martech systems, ensuring insights drive automated action.

Translate data science outputs into clear, actionable business recommendations for Director and Vice President level stakeholders.

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.

7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.

Experience deploying ML models into production environments.