Project Manager, Data Automation - job 2 of 2

As a Project Manager in Data Automation at Talent Worx, your responsibilities include interpreting project requirements, developing project plans, and leading the complete execution of projects. You'll engage with business leads, manage relationships, ensure service quality, and participate in evaluating machine learning solutions, all while collaborating with various stakeholders and vendors.

To qualify for the Project Manager, Data Automation position at Talent Worx, candidates should possess 6-10 years of project management experience, particularly in data science, machine learning, and Gen AI/LLM projects. A degree in relevant fields like Computer Science, Engineering, or Data Science is preferred, and certifications like PMP or PRINCE2 are valued.

As a Project Manager, Data Automation at Talent Worx, you'll join a diverse and dynamic global team. You'll have the chance to collaborate closely with senior stakeholders, business operations, and technical teams, which enhances the project's success and fosters an atmosphere of learning and innovation.

In the Project Manager, Data Automation role at Talent Worx, you'll act as a bridge between technical teams and stakeholders. This involves clear communication of project goals, presenting strategic insights, and ensuring transparency while collaborating on solutions that drive value across the organization.

A Project Manager, Data Automation at Talent Worx should have strong communication skills, the ability to work in a multicultural environment, and a passion for continuous learning. Being open-minded and capable of driving initiatives with minimal supervision will significantly contribute to the project's success.

When answering this question, be sure to detail the project's objectives, your specific role, the technologies and methodologies used, and the positive outcomes achieved. Tailor your response to highlight your leadership in data automation initiatives.

Explain your approach to task prioritization, possibly using methods like the Eisenhower Box or Agile methodologies. Emphasize how you balance urgency versus importance and ensure that project milestones are met.

Provide examples of specific machine learning or data science projects you have worked on, mentioning the technologies used and the impact your contributions had on the project. Highlight how you keep up with the latest trends in this area.

Discuss your conflict resolution strategy, emphasizing active listening, diplomacy, and finding common ground. Share a specific example where you successfully navigated a stakeholder conflict to keep the project on track.

Reflect on a project where you identified inefficiencies and implemented changes that led to better performance. Discuss the steps taken and the measurable improvements experienced afterward.

Mention specific project management tools such as Trello, JIRA, or Microsoft Project, and any methodologies like Agile or Scrum that you are familiar with. Be prepared to explain how these tools and methods enhance project efficiency.

Discuss your techniques for understanding business objectives and communicating them effectively to your project team. Highlight how you engage stakeholders throughout the project lifecycle to maintain alignment.

Identify key skills such as communication, leadership, problem-solving, and adaptability. Provide examples of how you’ve applied these skills in previous projects to deliver successful outcomes.

Share your approach to nurturing vendor relationships, including clear communication, behavioral expectations, and how you effectively manage deliverables and timelines to ensure project success.

Discuss metrics and criteria you use to assess project success, including stakeholder satisfaction, project deliverables, adherence to timelines, and any lessons learned for future projects.