Manager, Insights Engineering & Innovation, Medical Affairs, Japan

Location: Chiyoda, Tokyo, Japan

Remote Type: Hybrid Work

Time Type: Full time

Job 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:

Medical Affairs Group

Job Sub Function:

Multi-Family Medical Affairs

Job Category:

People Leader

All Job Posting Locations:

Chiyoda, Tokyo, Japan

Job Description:

The Manager, Insights Engineering & Innovation will lead the insight analytic function within Medical Affairs (MAF), delivering timely, accurate, and actionable insights to inform strategic decision‑making. This role is also responsible for designing and operationalizing AI-driven solutions/automation (including GenAI and conversational AL) that produce measurable business outcomes. The successful candidate will combine hands‑on technical expertise (for example, data engineering, ML/NLP engineering, MLOps) with strong people and stakeholder management skills to scale reliable, compliant, and cost‑effective analytics and automation capabilities into production.

Core Responsibilities

·       Define and execute the insight analytics and innovation roadmap for MAF, ensuring alignment with organizational priorities and prioritizing initiatives by business impact and feasibility.

·       Lead the end‑to‑end lifecycle for AI, data science, and intelligent automation initiatives, including problem framing, data discovery, model development (e.g. traditional ML, deep learning, LLMs), validation, deployment, monitoring, and continuous improvement.

·       Build and operationalize GenAI/LLM and NLP capabilities: chatbot/voice-bot, retrieval-augmented generation (RAG), fine-tuning and continual learning, prompt engineering, evaluation frameworks (accuracy, confidence, explainability).

·       Ensure data integrity by establishing and enforcing standards for data quality, lineage, provenance, and documentation; implement best practices for reproducibility, version control, and change management.

·       Translate complex quantitative analyses into clear, actionable recommendations.

·       Partner with business stakeholders to identify high‑value automation/innovation opportunities, define success metrics, and measure realized business impact.

·       Collaborate with Capabilities & Digital Excellence team members to design, build, and maintain reports, dashboards, and self‑service analytics that enable data‑driven decision making across the organization.

·       Promote adoption of AI and intelligent automation across MAF by developing implementation playbooks, runbooks, and training materials.

·       Establish monitoring and governance for deployed models and automations, including performance tracking, drift detection, retraining triggers, and rollback procedures.

·       Manage cross‑functional delivery: coordinate with data engineering, IT, regulatory/compliance, and vendor partners to ensure secure, scalable, and cost‑effective deployments.

·       Mentor and develop analytics talent, fostering a culture of rigorous analytics, experimentation, and continuous improvement.

Qualification:

• Master, MBA, Data science, engineering or related major;
• Prior experience in pharmaceutical documentation processes and medical liaison activities preferred.
• Hands‑on experience with data engineering/science, analytics, MLOps, and cloud data platforms (AWS/Azure).
• Strong SQL and Python skills, ETL/pipeline design, familiarity with data visualization tools (tableau, PowerBI) and model monitoring frameworks.
• Excellent analytical and problem-solving abilities.
• Practical experience with NLP and GenAI (LLMs), including RAG, fine-tuning, prompt engineering and evaluation.
• Experience building conversational AI (chatbot and voice bot) solutions end-to-end.
• Demonstrated experience deploying AI/automation solutions in regulated environments and managing stakeholder expectations at senior levels. 
• Excellent communication, project prioritization, and leadership capabilities.
• Project management and/or process excellence skills are an advantage

JOB SPECIFIC COMPETENCIES/SKILLS REQUIRED:

• Exceptional communication, presentation, and stakeholder management skills in both Japanese and English.
• Deep understanding of ML/AI frameworks and tools (NN, CNN, LLM, PyTorch/TensorFlow, Transformers, vector search)
• Strategic agility, Digital analytics & omnichannel, Presentation skills and business acumen desirable
• Adherence to, Johnson & Johnson Credo values and International Health Care Business Integrity Guide

< For Internal Applicants >

• Based on your experience and interview evaluation, the position title and level may vary.

• If you are Japan employee, please read “Internal Application Guideline” in Ask GS. Especially if you are less than 18 months in your current role, you are required to obtain application approval from your current manager as well as your respective BUHR. If you are Japan’s employee, you are not able to apply for multiple positions at once.

• For Employee Referral Program (ERP), please read and understand the details of the “Internal Referral Overview” on the Ask GS and you have made a compliant referral.

 

 

Required Skills:

 

 

Preferred Skills:

Analytical Reasoning, Business Planning, Business Savvy, Clinical Research and Regulations, Clinical Trial Designs, Clinical Trials Operations, Developing Others, Fact-Based Decision Making, Health-Medical Programs, Inclusive Leadership, Leadership, Medical Affairs, Medical Communications, Resource Allocation, Stakeholder Engagement, Strategic Thinking, Team Management