Senior Manager, People Analytics Generative AI Platform - job 13 of 21

As the Senior Manager, People Analytics Generative AI Platform, your key responsibilities will include defining and managing the implementation of the Generative AI strategy and product roadmap, developing innovative chatbot solutions, and measuring their impact through defined ROI metrics. You’ll oversee the product lifecycle, from initial concept to deployment and maintenance, collaborating closely with the People Technology team to ensure success in an agile environment.

To qualify for the Senior Manager, People Analytics Generative AI Platform role, candidates should have extensive experience in product management, with a strong focus on Generative AI applications. A solid understanding of the agile methodology, JIRA tools, and experience in leading cross-functional teams are crucial. Additionally, a background in HR analytics and a passion for enhancing employee experiences through AI technology will set you apart.

The Senior Manager, People Analytics Generative AI Platform significantly enhances employee experiences by developing innovative generative AI solutions that simplify how employees interact with data. By driving the development of chatbots and other AI-based applications, you’ll create tools that provide better insights and support for employees, ultimately fostering a more connected workplace.

In the role of Senior Manager, People Analytics Generative AI Platform, familiarity with agile methodologies is essential. Additionally, being proficient with JIRA tools for project tracking will aid in managing product development efficiently. Staying updated on AI trends and machine learning principles will also be crucial for continual platform improvement.

This position is a hybrid role based in Austin, where the expectation for time spent in the office will be confirmed by your hiring manager. This dynamic work environment blends in-person collaboration with the flexibility of remote work, helping you balance productivity and teamwork effectively.

When asked about your experience managing AI projects, focus on specific examples of previous projects you led, the challenges faced, and how you ensured alignment between technical teams and stakeholders. Highlight your familiarity with managing timelines, resources, and budgets, as well as your ability to drive innovation through AI.

To effectively measure the success of generative AI solutions, discuss your approach to defining key performance indicators (KPIs) and return on investment (ROI) metrics. Consider including examples from past experiences where you tracked usage metrics, user feedback, and improvements in employee engagement as measures of success.

When prioritizing product requirements, explain your method for engaging stakeholders to understand their needs thoroughly. Discuss utilizing frameworks such as the MoSCoW method or other prioritization techniques to ensure that the most impactful features are developed first, balancing stakeholder input with business objectives.

Be prepared to discuss potential challenges such as resistance to change from employees, data privacy concerns, and ensuring integration with existing systems. Emphasize your proactive approach to addressing these challenges, perhaps through communication strategies, change management plans, and user training programs.

When answering about staying updated on trends in AI and machine learning, mention your routine habits such as following industry blogs, attending webinars, participating in professional networks, and engaging in ongoing education to maintain a competitive edge in Generative AI applications.

Share a specific example of a project where you led a cross-functional team, outlining your role and the project’s objectives. Explain how you facilitated communication among team members with different expertise, overcame any conflicts, and ensured the project met its deadlines through effective teamwork.

Mention your familiarity with project management tools like JIRA, Asana, or Trello. Explain why you prefer these tools, based on their capabilities for tracking and reporting project progress, facilitating team collaboration, and ensuring transparency in the workflow.

When asked about defining product vision for generative AI solutions, emphasize your approach to gathering insights from user feedback, understanding market trends, and aligning objectives with business goals. Discuss how you translate this information into a clear and compelling product vision that guides development.

Discuss your comprehensive approach to managing product lifecycles, noting the importance of initial research and development, ongoing maintenance, and incorporating user feedback for iterative improvements. Highlight your focus on maximizing the value delivered to users throughout all phases of the product lifecycle.

When supporting change management after launching a new AI product, explain your strategies for communication, training, and soliciting feedback. Emphasize the importance of onboarding sessions, creating resource materials, and maintaining an open dialogue for ongoing adjustments that enhance user adoption.