Manager Talent Insights Advanced Analytics

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

Job Function:

Job Sub Function:

Job Category:

All Job Posting Locations:

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

The Manager TI Advanced Analytics will partner with the Global Talent Acquisition organization and People Analytics leadership to advance data and talent analytics capabilities, products, and services across J&J globally. 

Qualifications  

• A minimum of a Bachelor's degree is required. Master's degree or PhD is preferred.
• A minimum of 8 years of experience in leading data science and analytics projects. Utilization of the full stack of data science tools is preferred (SQL, Python, Tableau).
• Demonstrated knowledge in data science tools is required; tools such as Cloud IDEs, Cloud storage, Cloud computing platforms, Visualization software and automation software.
• Experience in judicious use of compute, cloud storage and bandwidth in projects is required.
• Experience in the full project lifecycle, inception, conceptualization, iteration cycles, deployment and after-action reviews is required.
• Demonstrated experience in stakeholder management in a matrix organization is required. Strong communication skills are a must for executive connects and engagements.
• People leadership experience is required. Experience in leading 3 or more technical team members is preferred.
• Required to have the ability to bring to life data and analytics to drive actionable business insights.
• Having a sizeable portfolio of projects that demonstrate leading data science initiatives for customers and clients is preferred.
• Experience in a global services setting or consulting for internal teams and/or clients is preferred.

Reporting directly to the Senior Manager, Talent Insights; the Manager TI Advanced Analytics will be responsible for:
 

People Leadership:

• Hire, retain and engage experienced analysts to advance the data science agenda of TA.
• Train team members in the most suitable technologies and methodologies for data science.

Project Management:

• Manage the overall portfolio of projects for all products that TI Advanced Analytics will deliver. Systematically manage, oversee, and prioritize multiple projects and activities, while triaging ad-hoc requests. Conduct After Action Reviews (AARs) for all projects.
• Innovate and deliver analytics and insights needed for Quarterly Business Reviews.
• Own the democratization of external talent insights for TA, BUHR, and Hiring Managers via dashboards and other data science products.

Stakeholder Management:

• Facilitate stakeholder engagement to ensure the business value of TI data science products and initiatives.
• Connect with other leaders within and outside of TA to stay updated on current trends, needs within the organization, and developments in the data science and business space.

Technology and Data Science:

• Ensure full data science stack capability (Acquisition, Engineering, Storage, Analysis, Visualization).
• Ensure the readiness of the team to integrate and maximize AI within workflows and products.
• Stay current with leading external analytical capabilities and bring new knowledge into the organization. Maintain a good understanding of the latest data science technologies to iteratively improve the tech stack, architecture, and implement new libraries for more effective capabilities.
• Acquire and assimilate technologies and platforms to enhance Data Science and AI capabilities.
• Oversee external talent data sources and platforms.
• Drive continuous improvement through agentic AI and intelligent automation to fully automate tasks performed by machines.
• Champion data integrations across diverse data streams in HR.
• Ensure compliance of the projects through data and tech governance.