Behavioral

Can you tell me about a project you are proud of?

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Answers

Anonymous

6 months ago
4.6Exceptional
Project: One project I’m particularly proud of is a Python-based trading system I developed for pairs trading. This market-neutral strategy aimed to exploit pricing inefficiencies between two correlated stocks by taking long and short positions based on daily stock returns.
Why I’m proud: Building the system from scratch was a challenging but rewarding experience that required me to apply my programming and statistical analysis skills in a real-world context. One of the main challenges I faced was identifying stock pairs with high correlations while ensuring that the strategy remained robust across different time periods. I overcame this by conducting extensive backtesting, using 4.5 years of in-sample data and 6 months of out-of-sample data, to validate the system’s performance. The results were promising, even though I hadn’t factored in transaction costs yet, which provided valuable insights into the strategy’s potential.
Additionally, this project pushed me to deepen my understanding of quantitative finance, especially in areas like risk management and statistical modeling. While I worked independently on most of the system, I also consulted with a few peers for feedback on the model's assumptions, which improved its overall design. This project not only reinforced my technical skills but also enhanced my problem-solving and critical thinking abilities, making me more confident in tackling complex financial models.
In summary, this project was significant because it challenged me to think critically, apply technical skills in a practical setting, and collaborate with others for feedback—all of which I believe are highly relevant to the role I’m applying for.

Anonymous

10 months ago
4.6Exceptional
Im most proud of one of my recent projects - architecting an event-driven system for caching analysis outcomes, building a microservice to vend the outcomes while also migrating existing data from DynamoDB to OpenSearch.
Reasons:
1. The existing data model was limiting in that it was not extensible to cache other NLP analysis  outcome except translation for which it was built initially. This made the system not usable for other newer use cases. I designed a new data model that was generic and extensible to other analysis and allowed caching of other results
2. Opensearch was a technology unfamiliar to our team and it involved a steep learning curve for me and other people who worked on the project. I made sure I documented any new learnings/choices so it was easier for the other team members to pick up and work on it. I setup separate sessions with the other 2 engineers who worked on it to go over some details like VPC, how private links are setup etc to unblock them
3. I setup CI/CD pipelines and automated testing.
4. Setup metrics and alarms through Infrastructure as code
Result:
We were able to launch the project within tight deadlines
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Interview question asked to Data Scientists, Solutions Engineers, Technical Program Managers and other roles interviewing at Credit Karma, Jobvite, DigitalOcean and others: Can you tell me about a project you are proud of?.