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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.

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The majority of the features we implement is on the customer feedback with exception to maybe health, monitoring, and non functional requirements of the product for example performance.

Right now, we are working on addining AI summaries for additional languages, we were focusing on english but this requirements came from global enterprises we are working with as well as from our strategic roadmap to increase customer acquisition by expending the customer base to non English speaking countries as well it aligned with our go to market strategy to go through partners and channels in different and many in Europe countries. 

I use a structured approach to prioritizing features. For each of the features, I analyze the impact, urgency, strategic goal alignment, cost vs effort.

Impact - I evaluate the number of customers or which customer segment  these features would benefit or evaluate if this feature mitigates any existing risks. I will also analyze if the features impact short term or long term goals. For Example - A feature addressing a customer pain point would take a higher precedence over a performance issue if a temporary workaround is available. Although the performance issue fix will benefit in the long term, but it can be deferred to a later sprint.

Urgency - I would evaluate to see if any of the features comes with a

Tight deadline - For ex - PCI Compliance. This would make this feature a higher priority as without a compliant software you can’t exist in the market.

Competitive advantage (Opportunity Cost) - If the feature is critical to getting a competitive edge then this feature should be prioritized higher as sometimes delaying on an opportunity cost has a higher loss.

Strategic Goal Alignment - Evaluate the tasks against the business goals in place like - Revenue growth, retention rate, CSat. If any of the features directly contribute to the goals then they would take higher precedence. There has to be a balance between short term and long term alignment here as well.

Team effort - In collaboration with cross functional teams, the effort to build a feature should be considered. A high reward feature with lower efforts should be prioritized before a low reward, high effort features.

With this approach I build my prioritized list of features for developement.

When thinking about market value, it's important to think about the total addressable market. I see four major types of users:

1. Professionals who need a high degree of mobility - Police and security, Couriers, etc.

2. Tourists who want a special experience and to cover much ground.

3. People who need assistance with mobility.

4. Tech forward adopters who want to always use the latest technology and gadgets, but who aren't necessarily required to have them to function day-to-day.

While these groups are not mutually exclusive, their needs and drives are quite different.

Next I would want to think about the US population that's available for each of these groups. From this list, I'd want to prioritize Professionals and those with Mobility. They are both durable users who will regularly use a solution. Tourists are occasional users. And tech early adopters are a smaller group due to requiring high discretionary income. 

While mobility could open up some new product potentials, and have a different funding source (e.g. insurance providers) I'm going to set them aside and focus on professionals.

Within the professional group, I'd further break it down to outdoor / indoor users and professional / private users. Next, I'd try to define the market size potential for each. This would be influenced by the context and ability to buy Segway products or get company or governments to pay for them. 

From there, I'd figure out the total addressable market for Segway products, make an assumption about penetration rates and net income per user, and apply a multiple to come up with the total market value.

I led a project to implement a new feature in our loan processing system aimed at reducing API latency for faster loan approvals. Midway, I encountered data inconsistencies and latency issues caused by schema mismatches between the new API and our backend services. To resolve this, I optimized the data schema mapping, streamlined query performance, and introduced Redis caching for frequently accessed data, which significantly reduced the API call frequency and improved response times.

I also collaborated with QA to parallelize testing, allowing us to catch issues early. By continuously optimizing our microservices with adjustments to load balancing and asynchronous data processing, we increased processing speeds by 20%. While the deadline was slightly extended, our enhancements directly improved loan approval times and were a solid technical win for both the team and the user experience.

Situation:One product I love is Spotify. It’s my go-to platform for discovering new music, creating playlists, and enjoying podcasts. However, despite its strengths, I’ve noticed that the music recommendation algorithm, while good, sometimes lacks the depth to truly capture my evolving tastes over time, especially for niche genres.

Task:Given the opportunity to improve Spotify without any limitations in engineering or financials, my goal would be to enhance the recommendation system to deliver more personalized and dynamic music suggestions, tailored to the user’s unique and changing preferences.

Action:I would introduce an AI-driven recommendation engine that leverages deep learning and user sentiment analysis. The system would analyze not just the songs users listen to but also contextual factors like mood, time of day, weather, and even activities (e.g., working out, studying). I’d also integrate voice recognition technology, allowing users to describe what they’re in the mood for, and the AI would instantly generate a playlist based on that input.

Additionally, I would enhance the social aspect by creating a feature where users can blend their music tastes with friends in real-time, generating collaborative playlists that adapt as they listen together.

Result:This improvement would create a more immersive and personalized experience, with Spotify becoming a true companion in understanding and anticipating musical needs. Users would discover more relevant music and podcasts, increasing engagement and satisfaction. The platform’s ability to adapt to each user’s evolving preferences would set it apart from competitors, driving further user retention and growth. The social feature would deepen community interaction, making Spotify not just a music app, but a shared experience.

At my previous job, the development process moving slower than expected at my first project since I was not familiar with the development progress.

When I realize this situation, I tackle this problems with some actions: (I took proper action afterwards:

1.First, I start by thorough understanding the development process and test plan, which associate the function test case, requirement and criteria for each phase. Those could let me planning the design schedule accurately, andarrange the test resource more efficiency.

2.On the other hand, to set the check point for project review

3.For issue management, provide the issue summary which include isolation result, impact and mitigation plan for risk assessment for further control. Take partial review with team members in order to ensure could meet target performance in tight schedule.

Both give me the precise control for development and test area, and could identify potential risk in advance, be able to have recommendations for improvements as well.

After that, I have in charge for more than 15 projects and achieve 94% timely delivery of high-quality results.

Alsoability to manage multiple projects simultaneously.

I once led a restructuring initiative aimed at aligning resources with delivery accounts and redesigning KPIs. While the planning and communication strategy were solid, I overlooked whether our data platforms could support the new changes. Just before rollout, I discovered serious data integrity issues. This setback required a major clean-up effort across teams, but we corrected course by prioritizing platform readiness and enhancing our validation processes for future initiatives.