Sr. Applied Scientist / Sr. ML scientist, EU Prime and Marketing Analytics & Science (PRIMAS)

Amazon Jobs; Barcelona; Presencial; EUR 70.000 - 90.000; Jornada completa

Descripción de la vacante

A leading global e-commerce company in Barcelona is seeking a Senior Applied Scientist to lead the lifecycle marketing strategy and experimentation roadmap. The role involves advanced modeling techniques, mentoring a team, and influencing stakeholders. Ideal candidates should have a Ph.D. in a quantitative field, with over 7 years of applied machine learning experience. The company promotes diversity and is committed to providing an inclusive workplace for all employees.

Formación

• 7+ years of experience in applied machine learning and customer analytics.
• Experience with experimental design principles and causal inference techniques.
• Track record of defining science strategy for new problem spaces.

Responsabilidades

• Own the end-to-end science strategy for lifecycle marketing.
• Build sophisticated propensity models for customer cohorts.
• Partner with measurement scientist to design experiments that isolate audience targeting effects.

Conocimientos

Advanced modeling techniques

Customer lifecycle marketing

Technical leadership

Data science

Influencing senior stakeholders

Educación

Ph.D. in a quantitative field

Herramientas

Machine learning

Data analytics

Descripción del empleo

Are you interested in defining the science strategy that enables Amazon to market to millions of customers based on their lifecycle needs rather than one-size-fits-all campaigns? We are seeking a Senior Applied Scientist to lead the science strategy for our Lifecycle Marketing Experimentation roadmap within the PRIMAS (Prime & Marketing analytics and science) team. The position is open to candidates in Amsterdam and Barcelona.

Key job responsibilities

Science Strategy & Leadership

• Own the end‑to‑end science strategy for lifecycle marketing, defining the roadmap across audience targeting, behavioral modeling, and measurement.
• Navigate high ambiguity in defining customer journey frameworks and behavioral models – our most challenging science problem with no established playbook.
• Lead strategic discussions with business leaders translating business needs into science solutions and building trust across business and tech partners.
• Mentor and guide a team of 2‑3 scientists and BIEs on technical execution while contributing hands‑on to the hardest problems.

Advanced Customer Behavior Modeling

• Build sophisticated propensity models identifying customer cohorts based on lifecycle stage and complex behavioral patterns (e.g., Bargain hunters, Young adults Prime prospects).
• Define customer journey frameworks using advanced techniques (Hidden Markov Models, sequential decision‑making) to model how customers transition across lifecycle stages.
• Identify which customer behaviors and triggers drive lifecycle progression and what messaging/levers are most effective for each cohort.
• Integrate 1P behavioral data with 2P survey insights to create rich, actionable audience definitions.

Measurement & Cross‑Workstream Integration

• Partner with measurement scientist to design experiments (RCTs) that isolate audience targeting effects from creative effects.
• Ensure audience definitions, journey models, and measurement frameworks work coherently across Meta, LiveRamp, and owned channels.
• Establish feedback loops connecting measurement insights back to model improvements.

About the team
The PRIMAS (Prime & Marketing Analytics and Science) is the team that supports the science & analytics needs of the EU Prime and Marketing organization, an org that supports the Prime and Marketing programs in European marketplaces and comprises 250‑300 employees.

The PRIMAS team is part of a larger tech team of 100+ people called WIMSI (WW Integrated Marketing Systems and Intelligence). WIMSI’s core mission is to accelerate marketing technology capabilities that enable de‑averaged customer experiences across the marketing funnel: awareness, consideration, and conversion.

Requirements:
- Experience working with and influencing senior level stakeholders
- Ph.D. in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science, or experience in data science, machine learning or data mining
- Experience working effectively with science, data processing, and software engineering teams
- Experience in customer lifecycle marketing or partner marketing management
- Applied Scientist with 7+ years of experience in applied machine learning and customer analytics
- Track record of defining science strategy for new problem spaces
- 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

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice https://www.amazon.jobs/en/privacy_page to know more about how we collect, use and transfer the personal data of our candidates.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.