The most comprehensive bank Interview Answer Review tooling available online.

One project i'm proud of is my internship project which was a full stack project where i had the chance to create a prototype of a template manager , storing the data into a cassandra database, alongside using springboot and java to work on the module structure and life of the project, I then used js and react for UI. This prototype was then deployed and is now being used by internal payment team at jpmc, instead of going to search every resource, i store all the templates in one template manager and they can know just search the nav bar and get the exact template they need. I'm proud of this project not only because it was my first real project using the new languages and frameworks i was learning during internship but it also gave me the confidence of knowing and seeing that I can do this even though i dont have a degree in this field!

I would establish a priority list dependent on the impact each ask has on the company.  The higher the impact, the higher the priority.  I would assess how long each ask takes and then speak with the stakeholders letting them know that I support their ask.

In my current role, there was a time when operation and engineering team was not aligned which was causing lots of delays during deployment. as per operation team build should be deployed in same branch which was available on pre-prod but as we were running multiple projects/features parallelly. it was difficult to develop and test everything in one branch and made it ready for deployment in a short time.

I had to work with my team (engineering team) and operational team to come up with a solution where we both are aligned and can reduce delivery time as well.

Initially i had proposed a solution when we were developing and testing work on feature branch and once its fully tested by QA on feature branch we push all changes to staging branch where we can do final testing. for some time this approach worked but we start facing new issue which is related to code merge as after merge features were impacting each other and require additional time to fix those issues and make it ready within planned time.

We added one more process if features/fixes are small and won't impact much then we merge else we try to plan deployment sequentially to avoid any further delay. 

This approach helped team to deliver project/feature on time and operational team was happy as they don't need to keep track of multiple branches during deployment.

In my early days as Program Manager, I managed a project for one of our main customers. This project had a very tight schedule and I promised to deliver the first EVT samples in 3 months.

It was my responsibility to ensure everything would be completed on time, and achieve the quality standards defined by the program and inside the budget approved by leadership.

Unfortunately… when I started to deep dive into the project and analyze all the technical details, I realized that it was not possible to get the prototypes ready on time. I missed the deadline by 2 weeks. I felt bad at that time because I failed, so I immediately started to work on a new feasible schedule trying to mitigate the problem. In addition, I arranged a daily opening and closing meeting with the core team to monitor all activities. The root cause of the problem was a delay in some component's delivery and I also ignored one of the Reliability tests defined by Engineering.

So I highlighted the problem to my manager and I shared with him my new plan. I explained the situation to him and I shared the new timeline that I could meet. Then we worked together to commit to the new delivery date. So I learned a lot from that situation, now I’m always adding some buffer to my project schedules and I work more closely with core team members. But the most important learning was, how important is to be honest and raise your hand on time if something goes wrong.

In the Meraki integration project, the supply chain process required significant optimization of the entire flow. To achieve this, most of the shipping-related process needed to be modified. However, the team lacked sufficient time to complete the work because the planned use of an adapter did not work, requiring me to redesign the flow.

With limited time remaining before system integration testing (SIT), the cross-functional teams and other tracks were ready to test their code, and management was unwilling to postpone SIT and Cycle 1 testing. Since there was an additional round of SIT and Cycle 2 testing planned, I decided to proceed with the changes that the team had already completed. We migrated the completed code to the test instance and communicated that only Phase 1 of the changes would be released initially, while the remaining changes would be delivered during Cycle 2 testing.

I ensured the Phase 1 delivery was designed to avoid impacting the end-to-end flow, allowing the other teams to proceed with testing their portions of the code. This approach ensured that other teams' deadlines were not affected. I also informed the cross-functional teams that the OTM and GTM changes were completed, and the remaining shipping-related code optimization would be delivered before Cycle 2 testing, along with the next round of SIT.

By taking this approach, I ensured that complete testing was not impacted and that the project stayed on track.

Situation: During the first calibration of Non-Maturity Deposit (NMD) models, I was working with a senior colleague and a consultancy firm to implement these models. At that time, market rates were rising, and the consultancy firm suggested calibrating a key parameter, the "beta," to be highly sensitive to market rates. My manager agreed, but I disagreed, as I believed this high sensitivity could lead to inaccurate estimations in future calibrations.

Action: I engaged in discussions with my manager and the consultancy firm to fully understand their reasoning. They argued that a more sensitive beta could improve management of metrics like Delta EVE and Delta NII, which was valid. However, I pointed out that we lacked sufficient evidence to support such a high beta and that it might cause issues in future estimations. To address the disagreement, I conducted a sensitivity analysis, testing the model under various market rate scenarios.

Result: The sensitivity analysis helped us reach a compromise. We agreed to lower the beta, ensuring more stability in the model's performance. This adjustment allowed for a smoother transition of the parameter, ultimately improving the model's reliability while maintaining good risk management practices.