INFORMS Open Forum

Location: Bangalore, India

GE is the world's Digital Industrial Company, transforming industry with software-defined machines and solutions that are connected, responsive and predictive. Through our people, services, technology and scale, GE delivers better outcomes for global customers by speaking the language of the industry.

The Digital Research Lab at GE Global Research, Bangalore is dedicated to using Machine Learning, Operations Research and Natural Language Processing methods for developing state-of-the-art algorithms for fusing and processing multiple sources of information (operational data, sensor data, physics, weather, text, images, domain knowledge). The expanding group currently has more than 15 members with most having doctorates and/or international experience and with expertise in Machine Learning / Operations Research / Natural Language Processing. 

GE is an equal opportunity employer, offering a great work environment, challenging career opportunities, professional training and competitive compensation.

Highly motivated self-driven researcher in Operations Research / Machine Learning / NLP to be part of multi-disciplinary project teams addressing key challenges for different GE businesses.

As a member of the Digital Research team, you will work on projects to invent and develop predictive modeling and decision technologies for diverse GE businesses such as GE Aviation, GE Power and GE Healthcare. You will build machine learning and/or operations research models, applications and solutions to enable GE Businesses operate in an efficient manner. Some examples include building scalable decision algorithms from heterogeneous data such as time series data from sensors, physics models, weather data, text, images etc. You will need to collaborate closely with GE business counterparts and GE customers to understand their requirements and develop technology-based solutions to meet their needs. Typical applications include asset performance management, operations optimization, resource scheduling, network optimization, forecasting, early warning systems and supply chain optimization.  

Candidates should hold a Ph.D. in a relevant mathematical or quantitative discipline with an excellent academic record. Exceptional MS candidates with demonstrated ability to apply ML / OR / NLP technology to solve complex Business problems will also be considered. Should have deep knowledge in at least one area of analytics with practical experience in applying the techniques for solving industrial problems.  Strong programming skills in Python / R / Java is a must. Excellent communication and presentation skills are expected.