Manager, AI Products

Johnson & Johnson Johnson & Johnson · Pharma · Titusville, NJ +1

Manager, AI Products role focused on driving the evolution of business through AI/ML digital products for commercial, medical, and patient engagements, with an initial focus on Omni-channel programs. This role involves translating business needs into advanced analytics solutions, collaborating with various commercial and technical teams, overseeing AI/ML product processes, and applying AI/ML techniques to drive revenue growth and improve the commercial model. Requires experience with large pharmaceutical datasets and translating technical findings for non-technical audiences.

What you'd actually do

  1. Drive clear and effective business translation of AI/ML products between business and technical stakeholders.
  2. Lead collaboration with partners across Marketing, Sales, StAT and Data Science teams to incorporate market research, strategic imperatives, competitive intelligence into AI products to influence key decisions and brand strategy.
  3. Oversee the critical processes and resources that drive AI/ML products across brands. This includes leading contracted resources, prioritizing product enhancements, continuous process improvement/automation, and conducting quality checks on outputs.
  4. Expertise applying AI/ML machine learning, quantitative methods, predictive modeling and other analytics frameworks and techniques is required
  5. Experience with AI/ML enabled digital product development in a commercial, medical affairs, scientific affairs and/or R&D environment is required

Skills

Required

  • B.S. in Computer Science, Information Systems/Technology, or equivalent field
  • 5 years of relevant business experience in analytics, management consulting, project management or equivalent field
  • practical application of predictive modeling
  • translate technical findings for non-technical audiences
  • Excellent written and verbal communication skills
  • project management expertise
  • executive presence
  • Skilled in data extraction and summarization from large datasets using SQL
  • basic statistical analysis using preferred languages (i.e., Python, SQL, R)
  • Ability to translate business questions into fit-for-purpose analytical solutions
  • interpret outcomes of data science models into meaningful business insights and actionable recommendations
  • Influencing and facilitating effective internal communications and collaborations in a matrixed and fast-paced environment

Nice to have

  • MS / MBA
  • commercial experience
  • Extensive hands-on experience with large pharmaceutical data sets, including medical and pharmacy claims, specialty pharmacy data, patient services and sales datasets (e.g., DDD, HUB, XPonent, IQVIA, SHS, MMIT…etc.)
  • Demonstrated understanding of omnichannel marketing, especially within the pharmaceutical industry
  • Intellectual curiosity and passion to learn new things!

What the JD emphasized

  • AI/ML digital products for commercial, medical, and patient engagements
  • Omni-channel program for healthcare providers and patients
  • AI/Machine Learning techniques
  • AI/ML products
  • AI/ML machine learning, quantitative methods, predictive modeling
  • AI/ML enabled digital product development
  • AI/ML knowledge
  • predictive modeling
  • data science models
  • extensive hands-on experience with large pharmaceutical data sets
  • practical application of predictive modeling
  • translate technical findings for non-technical audiences
  • data extraction and summarization from large datasets using SQL
  • basic statistical analysis using preferred languages (i.e., Python, SQL, R)
  • translate business questions into fit-for-purpose analytical solutions
  • interpret outcomes of data science models into meaningful business insights and actionable recommendations
  • omnichannel marketing, especially within the pharmaceutical industry

Other signals

  • AI/ML digital products for commercial, medical, and patient engagements
  • Omni-channel program for healthcare providers and patients
  • AI/Machine Learning techniques
  • AI/ML products
  • AI/ML machine learning, quantitative methods, predictive modeling
  • AI/ML enabled digital product development
  • AI/ML knowledge
  • predictive modeling
  • data science models