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I will work with the Product Owners to define the feature , scope , timelines ,and proper definition of done , ready and define the timelines and value that is being delivered . Then work with the tech team to determine the solution approach and breakdown the feature in to high level stories / work breakdown into task determining the time & effort required to deliver it , sequencing the work in progress and trying to prioritize the work to incremental release and unlocking the cross dependency mapping the work for the alignment between both the teams - preparing the high level plan of execution with the timelines for dev + test + release in prod 

Parametric means that the underlying distribution of the data is typically normal, and assumes a specific data distribution. Parametric assumptions are required for tests like the two sample t-test, ANOVA, and pearson's coefficient. While non-parametric just means that the distribution of does not follow a specific "standard" distribution, (ie a heavy tail when a test assumes normal). Tests for these are typically Wilcox rank sum and etc

I see myself working at the intersection of engineering and quantitative finance ideally at a hedge fund such as Two Sigma. My past experiences at Harvard Medical School and internships at MITRE/rapStudy have given me an interest in creating scalable systems that are high performant and capable of ingesting large amounts of data for model development and research.  I strongly believe Two Sigma is the perfect place for me to work on these highly technical projects. Additionally, I also look forward to the prospect of entering leadership roles during my career, where I can play a more impactful role in prioritizing cultivation of engineering talent and projects in fields such as low-latency and data engineering.

I stand out because I combine operational depth with a transformation-focused mindset. At Mercer, I didn’t just manage benefit renewals—I identified inefficiencies and built solutions, like a global provider template that boosted data accuracy from 50% to 95%.

I also simplified complex reporting processes, saving over 15 hours per client while improving quality. What differentiates me is that I don’t wait for problems to escalate—I proactively redesign processes, engage stakeholders, and deliver scalable outcomes.

That mindset of continuous improvement and strategic thinking is what helps me make a lasting impact.

My philoshipy to build a high perfomance team is to create a bottoms up culture. By empowring my team members the autonomy of solving the customer problem which they deem fit at scale, they not only grow but also innovate on things if they don't like the status quo.

For e.g. At Auctane, one of my team members was not satisfied with the approach proposed for doing a sync of data from Microservices to monolith. He did a deep dive on how this can be improved, he proposed Kafka as a best fit stack we can use. I encouraged him to do a POC, come up with pros and cons. Then I set up a meeting with my director and did a POC, I talked about potential impact was not just for our team but could be implemented org wide as well. 

We implemented this new technology on the project he was working on, documenting all the learnings he discovred and released to prod. Once we were satisfied that it works for us, I arranged for a show/tell session for other engineeries who had to solve a similar issue, this developer gave a techtalk on how it was implemented, challenges we faced etc. Other teams adopted this tech as well. The result of this was that as an Org. we could save close to 15% of dev cycle by standardizing and implementing a new tech. My employee also took this opportunity to learn and grow at the same time.