Hrag Balian Email Address

Senior Vice President, Analytics and Data Engineering

Lieberman Research Worldwide (LRW) is a full-service, custom market research consultancy known for its ability to turn insight into impact for its clients. LRW employs a unique so what? research-based consulting model, leveraging its industry-leading Marketing Science team and Pragmatic Brain Science Institute to help clients improve their business performance. LRW conducts research in over 80 countries around the globe, addressing a range of issues, including market segmentation, brand strategy, marketing effectiveness, customer experience and new product development. We are honored to work for some of the biggest and best brands in the world.

I have spent my career unlocking the potential of data to drive business growth and innovation. With extensive experience in data strategy, engineering, and analytics, I excel at building highly productive technical teams that foster a collaborative culture. As the SVP of Analytics and Data Engineering at Material, I founded a team focused on MLOps, ML Engineering, and Data Engineering. I lead the development of products that reduce analytics labor, improve data quality, and promote data visibility. My experience includes architecting a Cloud data and analytics platform, designing scalable data pipelines, and developing APIs that democratize data access and improve analytic quality. With recent developments in LLMs, I've been leaning into AI enablement and rapid prototyping of data systems using Langchain and Streamlit. I have a background in Data Science where I built out new capabilities, led numerous studies, and consulted on advanced analytics. This experience allows me to not only understand technology but also the meaning behind data, enabling me to unlock its potential. My contributions include developing a new framework for customer journey mapping, generating $20M+ in annual revenue, and introducing cloud tooling to an analytics team, fostering a culture of innovation and continuous learning. My technical expertise is expansive, and spans across Python, R, Postgres, MongoDB, Athena, XGBoost, Scikit-Learn, PySpark, Terraform, AWS, GCP, Lambda, Fargate, ECS, Docker, S3, RDS, EFS, FastAPI, Flask, Plotly Dash, and Apache Airflow, among others. I hold a Ph.D. from Columbia University and have completed a Post-doc at Yale University. My deep-rooted interest in the underlying meaning of data stems from my Ph.D., where I built micro-models of social behavior. My doctoral dissertation revealed the striking similarity between large-scale armed conflict dynamics and conflicts among primitive animals, such as chickens, when establishing pecking orders. In my academic work, I received a number of awards and distinctions, including a Distinguished Dissertation, a Tilly Award for Excellence, and a Social Science and Humanities Research Council of Canada Doctoral Fellowship.