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Job Description
Structured overview of role & requirementsAbout This Role
Own end-to-end development and productionization of decision-support systems for marketing investment allocation, including response modeling, scenario analysis, and optimization.
Design and implement robust, high-performance APIs and scenario-optimization engines for stakeholder use across global brands and markets.
Collaborate across product, engineering, MLOps, and business teams to align AI modeling solutions with operational needs, ensuring adoption and maintainability.
Minimum Requirements
PhD in a quantitative discipline or Master's with 4+ years applied data science experience.
Strong expertise in AI/ML with hands-on experience in supervised/unsupervised learning, Bayesian statistics, and mathematical optimization techniques (LP/MILP).
Experience shipping production code and APIs in agile, product-focused environments, preferably with cloud computing platforms (AWS preferred).
Work Experience Required: Minimum 4 years analytical/applied data science experience if Master's degree; PhD holders not explicitly stated with experience requirement.
Ideal Candidate Profile
Experienced in marketing mix modeling, commercial analytics, recommender systems, or similar response and decision optimization problems.
Skilled in software engineering best practices with strong Python OOP, API development (e.g., FastAPI), CI/CD pipelines, and MLOps implementation.
Capable of translating complex technical and econometric modeling into actionable business insights for marketing and finance stakeholders in a global, cross-functional environment.