Neumo

Business Analyst

• Shadow employees, conduct structured interviews, and observe workflows firsthand to identify repeated, high-value knowledge work
• Document end-to-end processes: steps, frequency, time spent, data involved, decision points, and handoffs
• Classify which steps in a process can be fully automated (AI or software), which need human-in-the-loop verification, and which should stay manual
• Quantify the value of each automation opportunity (time saved, error reduction, throughput increase) so the team can prioritize effectively
• Prioritize the backlog of automation opportunities, working with the AI team leader to sequence what gets built
• Manage intake from the automation request portal, where employees across the company submit their own ideas for AI-powered improvements
• Track adoption and impact after automations are deployed, identifying what’s working and what needs adjustment
• Identify patterns across departments: if three teams have the same bottleneck, that’s one reusable solution, not three custom projects

AI Business Analysis Analyst III