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The Predictive & AI Manager designs and scales innovative, market‑ready predictive AI solutions that enhance commercial excellence and deliver incremental revenue and gross margin gains. The role owns end‑to‑end delivery of predictive AI use cases across global markets—from discovery and early data assessment through model development, deployment, rollout, and continuous improvement. In doing so, this role translates model signals into clear, ready‑to‑use recommendations, this role enables commercial decision makers to act with speed, confidence, and measurable impact.
Job Responsibility:
Partner with commercial decision makers to identify high-value opportunities and define predictive AI use cases, success metrics, data requirements, expected impact, and delivery approach
Execute complex EDA to validate feasibility, uncover key drivers, and translate insights into clear analytical requirements and implementation-ready specifications
Oversee vendor-led development and testing to ensure solutions meet defined requirements, acceptance criteria, and business-ready quality standards
Convert model outputs into actionable, ready-to-use commercial recommendations
Monitor post-deployment performance and adoption, detect drift or degradation, and drive vendor-supported enhancements to sustain accuracy, relevance, and commercial impact over time
Measure and report the business impact of predictive AI recommendations and use insights to drive continuous improvements through a prioritized backlog
Requirements:
Bachelor’s degree in Data Science, Statistics, Industrial Engineering, Software Engineering, or a related quantitative/technical field
Minimum 3 years of experience in roles applying predictive models to solve business problems and deliver measurable outcomes
Minimum of 3 years of experience in BI, reporting, descriptive/diagnostic analytics, or commercial analytics roles delivering analytics solutions that support business decisions
Proficiency in Python and SQL for data extraction, transformation, analysis, and model development
Demonstrated knowledge of supervised and unsupervised machine learning, supported by relevant certifications and/or formal training
Proven ability to translate complex analytics into clear, concise business insights and actionable recommendations for non-technical stakeholders
Strong stakeholder management skills, including the ability to influence without formal authority and drive alignment across teams
Excellent communication and interpersonal skills, with the ability to present technical concepts in business terms
Advanced Microsoft Excel skills, including complex formulas, pivot tables, data modeling, and analysis
Fluent in English (written and spoken) — minimum C1 level required
Nice to have:
Experience working in the pharmaceutical / life sciences industry
Exposure to or hands-on experience with agentic AI and/or large language models (LLMs)
Proficiency with business intelligence and visualization tools (e.g., Tableau, Power BI, or equivalent)
Familiarity with Agile delivery frameworks, including Scrum and/or SAFe (Scaled Agile Framework)