포지션 상세
At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.
• Build end-to-end with AI: Use AI to prepare data across sales, customer engagement, market and account sources, and to run exploratory analysis. Apply statistical and predictive methods where they add value, particularly across launch excellence, sales force effectiveness, brand strategy, and brand growth-driver analysis.
• Judge quality: Test results against alternative explanations, data artefacts and common analytical traps, and state how confident we should be and why.
• Deliver decision-ready insights: Turn the same insights into crisp narratives for leadership decisions and commercial organization actions, which today run on PowerPoint.
• Partner across North Asia: Act as the primary point of contact for North Asia stakeholders; partner with CE, BU, IT, regional and local teams to align market needs with regional strategy. Hold evidence-based positions with senior stakeholders and turn them into clear decisions and actions. Raise the team's way of working by sharing AI workflows, reusable components and templates.
• Heavy, hands-on use of AI in your own work — not only chat and summaries, but using AI to write and run analysis code, build tools and ship interactive outputs. Experience in agentic workflows is a plus.
• Comfort reading, running and debugging the code AI writes for you, in Python, SQL or R. Experience in prompt, context, and harness engineering is a plus.
• Solid statistics and analytical reasoning — enough to catch an analysis that is plausible but wrong (selection bias, confounding, leakage, wrong denominators).
• Structured problem solving: you can break a vague business question into hypotheses and an analysis plan.
• Clear communication with non-technical and senior audiences, in writing and in person.
• A degree in a quantitative field, or equivalent demonstrated rigour.
주요업무
• Frame the question: Take ambiguous commercial questions from North Asia markets — why uptake is lagging, which customers to prioritise, whether a campaign or resource shift is working — and turn them into a clear plan: which insights would change a decision, and what data can answer them.• Build end-to-end with AI: Use AI to prepare data across sales, customer engagement, market and account sources, and to run exploratory analysis. Apply statistical and predictive methods where they add value, particularly across launch excellence, sales force effectiveness, brand strategy, and brand growth-driver analysis.
• Judge quality: Test results against alternative explanations, data artefacts and common analytical traps, and state how confident we should be and why.
• Deliver decision-ready insights: Turn the same insights into crisp narratives for leadership decisions and commercial organization actions, which today run on PowerPoint.
• Partner across North Asia: Act as the primary point of contact for North Asia stakeholders; partner with CE, BU, IT, regional and local teams to align market needs with regional strategy. Hold evidence-based positions with senior stakeholders and turn them into clear decisions and actions. Raise the team's way of working by sharing AI workflows, reusable components and templates.
자격요건
• Typically 5+ years in advanced analytics, data science, consulting or a similar role, with insights that changed real business decisions.• Heavy, hands-on use of AI in your own work — not only chat and summaries, but using AI to write and run analysis code, build tools and ship interactive outputs. Experience in agentic workflows is a plus.
• Comfort reading, running and debugging the code AI writes for you, in Python, SQL or R. Experience in prompt, context, and harness engineering is a plus.
• Solid statistics and analytical reasoning — enough to catch an analysis that is plausible but wrong (selection bias, confounding, leakage, wrong denominators).
• Structured problem solving: you can break a vague business question into hypotheses and an analysis plan.
• Clear communication with non-technical and senior audiences, in writing and in person.
• A degree in a quantitative field, or equivalent demonstrated rigour.
