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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.

With a major product launch on the horizon, expecting to triple the user load. The infrastructure was non-optimized for demand and incident response was non-harmonious across teams with no set process.

As the SRE Manager, I'd have to implement project changes to infrastructure to accommodate high availability and scalability. I discovered a long-standing issue surrounding incident response and observability that would make it all the more difficult to achieve reliability under pressure and peak traffic.

Therefore, instead of fulfilling the project requirements as presented, I became an advocate for change across the organization. I established an observability platform with 100% stack coverage, created custom SLOs/SLIs/error budgets to enhance performance and reliability visibility, drafted and socialized an incident management playbook across the company and held hands-on trainings for all respective teams. In addition, I advocated for Terraform for Infrastructure as Code to help with deployment time and held FinOps reviews to help eliminate redundant costs in cloud spend.

As a result, we did not only survive the 3X traffic upon product launch with zero critical incidents, but we also achieved 15% saves the following years in cloud costs and 40% faster deployments. Many of the processes I created were adopted as company-wide best practices.