Ads team (from May 2024)

• Working as Senior product data scientist on Shopify Ads team helping product to identify next billion $ opportunities, deep dive statistical analysis & setting framework for extensive experimentation to iterate quicker. I lead couple of pillars within ads team (from data side) and collaborate with cross functional stakeholders (Product/Eng/UX) to help team reach our vision.

Retail team (from Jan 2023 to April 2024)

• Worked as a Senior full stack data scientist, I supported multiple teams within the Retail department, leveraging data to improve the merchant experience. One team focuses on creating back-office tooling for retail merchants, such as inventory management and fulfillment, while the other team works on extending the Shopify POS platform, enabling third-party developers to integrate with it.

Messaging team (from May 2020 to Dec 2022)

Started as Data scientist and then promoted as Senior full stack data scientist, As part of the Messaging team, which powers Shopify's 1P app, "Shopify Inbox", I led a sub-team that focused on driving product growth and increasing sales and conversions through conversational commerce. Leveraging data science techniques such as experiments and causal analysis, we identified key opportunities for growth and implemented solutions to optimize product performance.

One of my key accomplishments was developing a real-time streaming system that displays real-time buyer activities on the online store to merchants through the Inbox app. Leveraging Apache Beam, Kafka, and Google Dataflow, we built a scalable system that allowed merchants to stay informed of their customers' activities in real-time. Additionally, I developed a machine learning NLP system using Transformers and TensorFlow to categorize buyer messages into different topics, as well as a fast API service to support real-time decision-making. I also created a NER system using DistilBert to extract information from buyer messages.

• Worked on generating intelligent marketing recommendations for Shopify's merchant using Machine Learning which would provide them optimized budget and higher chances of conversion.

• Created Real time streaming pipeline that could provide signals to our Merchants inside Ping app whenever any buyer on their online store interacts with cart (adds/removes items). This is a very strong signal for merchant which helps them to priortize their replies and make overall conversation experience better. The technologies used are Apache Beam, Google Cloud Dataflow, Kafka streams

• Contributing to choosing which Machine Learning models to use and setting them up

• Preprocessing data to be in a format ready for the Machine Learning model (anomaly detection, normalizing)

• Taking ownership over certain datasets and being accountable for them being pre-processed accordingly

• Taking ownership over Machine Learning models, being accountable for their training, accuracy and tuning

• Contributing to the architecture of the code base.