ABOUT THE Role
Fueled by one of the largest sets of its kind in the region, the team at TabSquare is working on some of the most challenging and fascinating technology problems available right now in the restaurant industry. From personalizing the dining experience for restaurant diners by analyzing their past behaviors & interactions, to predicting restaurant occupancy based on weather and traffic conditions – we are using big to help change the way millions of people will dine at the restaurants and how restaurateurs will manage restaurant’s operations and engage with their restaurant patrons in the future. You, will be a part of “Restaurants 2.0” story! This is a unique opportunity to join a new, multidisciplinary team of creative and passionate individuals destined to change the face of the restaurant industry.
You will work with internal teams to support and contribute to the Restaurant of the future “Restaurants 2.0” vision for the company.Your focus is to research, investigate and execute smart restaurant concepts in Artificial Intelligence (AI) topics such as Deep Learning/Machine Learning, Optimization, demand forecasting, recommendation system and personalization within the context of the Restaurant of the Future. You will be on top of the development of machine learning models/predictive analytics techniques that optimizes Restaurant operations processes and reinventing customer engagement methods. In addition, you will have an opportunity on working through big problem from mining, cleaning, building concept of the model to support decision making through various analytic techniques and algorithm development involving unstructured and structured data. You will perform research on smart restaurant concepts and customer facing applications. You will be involved in technical planning, execution and delivery of development projects for global industry members. You will write technical reports and present technical results to internal teams and industry at large.
- Ph.D. or Masters in Computer Strong understanding of predictive modeling algorithms such as logistic regression, neural networks, SVM and decision trees
- Experience in building AI/ML models at scale, using real-time big pipelines on platforms such as Spark/MapReduce
- Familiar with noSQL, postGIS, stream processing and distributed computing platforms
- Working knowledge of Big technologies such as Hadoop, MPP Databases, or stream processing techniques
- Experience working independently and in a team
- Self-motivated, independent learner, and willing to share knowledge with team members
- Detail-oriented and efficient time manager in a dynamic and fast-paced working environment