Senior Applied Scientist / Senior ML Scientist (AI, Machine Learning)

TL;DR

Senior Applied Scientist (AI, Machine Learning): Leading the science strategy for lifecycle marketing experimentation, defining the roadmap for audience targeting, behavioral modeling, and measurement with an accent on API design, database performance, and scalability. Focus on navigating high ambiguity in defining customer journey frameworks, building sophisticated propensity models, and integrating diverse data sources for actionable insights.

Location: Must be based in Amsterdam or Barcelona, EU

Company

hirify.global is a division of Amazon focusing on accelerating marketing technology capabilities that enable de-averaged customer experiences across the marketing funnel.

What you will do

• Own the end-to-end science strategy for lifecycle marketing.
• Define the roadmap across audience targeting, behavioral modeling, and measurement.
• Lead strategic discussions with business leaders, translating business needs into science solutions.
• Build sophisticated propensity models and define customer journey frameworks using advanced techniques.
• Design experiments and ensure audience definitions and models work coherently across channels.
• Mentor 2-3 scientists and BIEs while contributing hands-on to complex problems.

Requirements

• Experience working with and influencing senior level stakeholders.
• Experience working effectively with science, data processing, and software engineering teams.
• Experience in customer lifecycle marketing or partner marketing management.
• Experience building machine learning models or developing algorithms for business application.
• Experience building and effectively executing a strategy from the ground up, including designing roadmaps to drive incremental progress towards long-term vision and goals.
• PhD in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or equivalent research experience.

Nice to have

• Experience with advanced modeling techniques (Markov models, sequential models, causal inference).
• Experience with experimental design principles and causal inference techniques.
• Technical leadership – ability to mentor scientists while contributing hands-on to complex modeling challenges.

Culture & Benefits

• Believes passionately that employing a diverse workforce is central to success.
• Values passion to discover, invent, simplify and build.
• Offers support for workplace accommodation or adjustment during the application and hiring process.