Description
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. Learn more at jnj.com.
As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.
Job Function:
Data Analytics & Computational SciencesJob Sub Function:
Business IntelligenceJob Category:
ProfessionalAll Job Posting Locations:
Chiyoda, Tokyo, JapanJob Description:
General Summary
The Manager, Online Data Analytics, will lead areas below under Sr. manager of performance marketing
- Support the development of online strategies through data integration and insight extraction.
- Lead and execute action processes that incorporate data-driven decision-making for the EC team, based on advanced analytics.
- Promote the development of data infrastructure, digital transformation, and digitalization initiatives.
- Set appropriate KGI and KPI, and implement PDCA cycles through tracking and continuous improvement
Duties & Responsibilities
- Partners with stakeholders to identify, scope, and execute analytics and digitalization initiatives that address key online business needs, resolve digital issues, and generate business value.
- Develops comprehensive data strategies that leverage both existing data (such as market data, platform data, media plan results, etc.) and new data acquisition efforts.
- Leads the planning and analysis of the online market landscape, collaborating with internal teams, external partners, and vendors to support the implementation of online strategies.
- Defines innovative trending and modeling techniques to analyze data, generate insights, and drive process improvements.
- Oversees and manages data quality assessment, data cleaning, and data processing practices.
- Partners with sales and platform teams by utilizing abundant data and insights to inform decision-making.
- Manages team performance and supports the development of team members.
Key Requirements (skills, competencies, experiences, certifications) /
Mandatory requirements
- Master's or Ph.D. degree in a highly quantitative field such as Machine Learning, AI, Computer Science, Statistics, Mathematics, or equivalent professional experience demonstrating advanced data science skills and knowledge.
- 5+ years of professional experience in data science, analytics, or business intelligence.
- Extensive knowledge of e-commerce and connected commerce, including data management and utilization, digital analytics tools, digital marketing, and technology architecture implementation.
Preferred requirements
- Ability to clearly understand business requirements and translate them into data-driven processes.
- Strong sense of responsibility and accountability to lead projects and deliver expected results by aligning with the company's vision, goals, and objectives while engaging team members and cross-functional stakeholders.
- Solid understanding of Big Data fundamentals, modern data ecosystems, and related technologies.
- Experience applying advanced analytical and statistical methodologies to solve complex business problems.
- Adaptable and flexible, with a willingness to learn and adopt new methods and ways of working.
- Ability to manage multiple tasks, budgets, and resources effectively in a fast-paced environment with competing priorities.
- Fluency in English, including excellent written, verbal communication, and presentation skills
Required Skills:
Preferred Skills:
Advanced Analytics, Business Intelligence (BI), Cross-Functional Collaboration, Data Analysis, Data Governance, Data Privacy Standards, Data Quality, Performance Measurement, Process Improvements, Tactical Planning, Team Management, Technical Credibility, Workflow Analysis