Refreshed Landing Page for Mobile App
Brief:
Encourage more nurses to create an account via the mobile app.
Pain Points:
- With the original flow prospective nurses would have to enter a phone number and then go through a five-step sign-up process, before seeing available shifts
- A Prospective nurse would not see any open shifts if their current location was more than 35 miles from the nearest facility.
Solution Architecture:
- We referenced landing pages for peer-to-peer apps like Airbnb and Uber for inspiration.
- We requested feedback from Account Managers who informed us that nurses in some remote locations could not see any available shifts
- I was in charge of helping the Business Analyst develop, translate, and test the requirements to the development team.
- Requirements included 1. Defaulting to current geolocation for the location field. 2. Listing the total number of facilities in the state with open shifts. Sorted by facilities that were closest, then by facilities with the most open shifts, and lastly by the highest par range. 3. If there were no open shifts in the user’s state show open shifts from the nearest state, to ensure users always see a facility card upon signup.
HEALTH METRICS FOR PREDICTABILITY
I pivoted from my QA Lead role to supporting the entire team as its Scrum Master in Sprint 31.
Brief:
- As Scrum Master, I Coached a team of 25 Frontend, Backend, and Fullstack engineers spread across 5 smaller Scrum Teams
Pain Points:
- Managing the team at large who were developing 3 new major in-app features simultaneously
1. New Geolocation based Pay feature
2. Migration to a new in-app payment processor
3. Airbnb style update to the landing page
- Led a team of 3 Manual QA's and 4 Automation Engineers helping them develop and document comprehensive manual/automated test plans, test scenarios, and test scripts.
- Onboarding a new QA Lead
- Working outside business hours to triage defects found post-release
Solution Architecture:
- Instituted a new testing initiative that saw a 200% reduction in regression and User acceptance testing time, by reducing the number of test environments that our code was deployed in.
- Improved our team’s velocity from 50 to over 200 story points completed on average per sprint by
- Improved our team’s predictability for stakeholders and marketing by creating a workshop on Estimating Story Points
- Implemented a feature flag toggle to hide new app features from certain users while enabling E2E testing in a production environment