I have been fortunate enough to have spent ~4 years working in data-centric roles in various industries.

My first role involving data was at SIG, a quantitative trading firm. Here, I worked on the energy trading desk: my job was to analyze electricity trading data coming in from exchanges into insights that the energy traders could use to make trading decisions. Electricity trading is vastly different from the conventional equity markets, mainly because of the fluctuations in pricing. For a detailed explanation, check out this piece by Neel Somani: he has done a really good job in explaining the concept.

• Technology Stack: Python (pandas, numpy, matplotlib), SQL, a little bit of Perl.

After my one-year stint at SIG, I joined forces with some friends in college to work on TruckBux (TBX for short), a startup born and incubated at my alma mater. TruckBux was conceived with the goal of bringing food trucks (a very common sight in Philadelphia) onto the online marketplace. Think of it as Uber Eats or Doordash for food trucks. At TBX, I was involved in setting up the analytics - metrics, KPIs and other insights that could be harvested from the data we collected. These metrics were used to monitor the overall health of the business, to help food truck owners generate more revenue, and seek venture capital funding. Unfortunately, the company does not exist in its original form anymore - it is now ZIKI Kitchen, a Greek-Mexican fusion food truck restaurant chain based out of Austin, Texas.

• Technology Stack: SQL, Metabase

I proceeded to work on the 4-person Product team at OODA Health, then a Series-A startup based out of Salt Lake City, Utah. Here, I was involved in developing better parsers for Electronic Medical Records (835 and 837 EMRs to be specific). I worked with engineers to improve our synthesis of EMRs. From a data perspective, I was involved in studying what factors affected the willingness of patients to pay their medical bills, analyzing debt collection rates and how the interactions between insurance-hospital-patients could be improved.

• Technology Stack: Python (pandas), SQL, Looker, Kibana

OODA was acquired by Cedar, a Series D unicorn based in NYC, for $425 million in the Spring of 2021. At Cedar, I worked as an Associate Product Manager on the Client Billing team. I worked alongside a team of engineers to build data products to assist in the reconciliation of health system invoices. We also built attribution models to accurately identify what payments flowing through our systems were eligible to incur product fees. In addition, I also had the wonderful chance of working with payment processing companies such as Stripe and WorldPay to build integrations based on their APIs to streamline our payments process. This job was heavily data-based, and transformative in shaping my approach to working with data.

• Technology Stack: Python (pandas), SQL, Looker (LookML + SQL), Snowflake, Airflow

I left Cedar in the summer of 2022 to pursue an analyst role at Amazon Fresh, which is where I work today. Here, I build analytics that help monitor the performance of vendors that supply to Amazon Fresh. This includes writing SQL, setting up ETL jobs, optimizing and refactoring SQL, in addition to publishing analytics detailing the health of vendors. In addition, I have also assisted in setting up the pre-requisite flows for a couple Machine Learning Projects.