Zaid Alibadi, Ph.D.

• Led the development of a real-time ranker for personalized product recommendations, driving $34.9MM in annualized sales. • Utilized Generative AI to build a product intelligence layer, enhancing catalog understanding and enabling new recommendation use cases such as project completers and basket builders. • Delivered a unified social proof messaging system that drove higher user engagement and customer trust, resulting in $100M+ in incremental revenue. • Developed an in-house “Sort By Relevancy” solution for product reviews, driving a 29-basis-point improvement in Add-to-Cart rates. • Managed and mentored a team of data scientists, fostering innovation and delivering $200M+ in incremental annualized revenue.

• Built and deployed a robust Offline Ranker framework using LightGBM’s LambdaMART, optimizing recommendations and driving $100M+ in annualized sales. • Designed real-time recommendation systems like “Visual Scout” and “Similar Items,” contributing to $60M+ in combined incremental revenue. • Enhanced cross-channel shopping experiences by integrating real-time candidate generation models and interactive tools, resulting in measurable improvements in CTR and CVR. • Collaborated with product managers and engineers to align machine learning solutions with business objectives. • Mentored junior data scientists, promoting a culture of excellence and continuous learning.

• Provided advanced analytical capabilities and implemented data-driven initiatives for Lowe's Companies, Inc. • Built production-ready recommendation engines, conducting end-to-end data processing, analysis, visualization, and algorithm development. • Increased the number of recommended items per carousel for all live items on lowes.com through a backfilling solution for Customer Also Viewed Recommendation. • Improved the relevancy and coverage of the Product Compare Module from 10% to 100% of total live items on lowes.com. • Developed solutions for cold start items and ranked product attributes based on customer importance. • Mined and extracted data, applied statistical methods and algorithms, and effectively communicated findings to various stakeholders. • Collaborated with cross-functional teams to drive audience and revenue growth through recommendation. • Utilized Python, SQL, Google Cloud Platform, Vertex AI, Hadoop, TensorFlow, scikit-learn, and Gensim.

• Provided data analytics for multiple marketing projects, involving data acquisition, cleaning, analysis, modeling, topic modeling, and data visualization. • Developed programs and services to support data visualization needs and worked with diverse datasets, including text and images. • Utilized Python, Pandas, Spacy, Gensim, Selenium, BeautifulSoup, Keras, Plotly, Scikit-learn, and Jupyter Notebook.

• Designed and implemented a hybrid mobile app, Chrome extension, and web app to help students track and manage scholarship applications. • Developed features for reminders, updates on application status, and tracking received scholarship amounts. • Utilized HTML, CSS, JavaScript, and Backendless.

• Managed and supervised a team of over 150 local national professionals, providing support to PAE digital and logistics operations at the US Embassy Compound, Baghdad, Iraq.

Utilizing Speech act theory, neural networks, word embeddings, and transfer learning to design and implement an intelligent email assistant to help email users managing the problem of email overload.

An executive format master's degree includes interdisciplinary courses in business, law, communication and engineering.