Research Scientist - General Motors (Bangalore, India)
General Motors Corp. (NYSE: GM), the world's largest automaker, has been the annual global industry sales leader for 76 years. Founded in 1908, GM today employs about 284,000 people around the world. With global headquarters in Detroit, GM manufactures its cars and trucks in 33 countries.
At GM R&D, innovation and market responsiveness are rooted in our history and form the foundation of our success. How does GM R&D carry on the tradition? By sensing the needs of diverse people around the globe and responding with imagination to meet those needs. We are constantly crossing the boundaries of science and engineering to benefit our customers and our world. You can tell by examining the scope of our work at R&D - jobs at GM R&D blend high-priority innovation programs, development projects, and exploratory research.
http://www.gm.com/
Job Description in brief-
The role is research base and requires people Statistics/ econometrics/ mathematics background. A top ranker in the BTech CS/EE/Physics class at an IIT, or a Math/Stats professor at a reputed school, or winner of an international programming contest is a plus. Candidates are specifically required to have current experience in statistical/econometric modeling on large data sets, or in the area of numerical analysis. Compensation exceeds industry standards.
Diagnosis and Prognosis Group (D&P)
Focus Area - Collect & analyze on-board real-time automobile data using data loggers, cleaning and filtering of the data, use the diagnostic trouble codes and vehicle sensory information to predict individual vehicle health, and prognosis capability to predict remaining useful life.
- Use of temporal data mining, fuzzy logic and neural net algorithms for real-time diagnosis and prognosis of vehicle components, sub-systems and system as a whole.
- Embed these algorithms inside the vehicle data logger for real-time vehicle heath management, anomaly detection via pattern recognition etc.
Communicate results in research reports and oral presentations within the company.
Experience: 1- 15 Years
Education: M.S. or PhD in Electrical Engineering, Mechanical Eng, Compute Science or equivalent
Mandatory Skill- Real-time data collection, data analysis and filtering
- Signal processing, pattern recognition, embedded systems, neural-net/fuzzy logic based prognosis and control of subsystems and systems. Background in physics based modeling for diagnosis and prognosis.
Remark: Any of the above mentioned skill is OK, depends on candidates years of experience
Diagnosis and Prognosis Group (D&P)
Focus Area- Data Mining and Analysis of Warranty and Service data for automotive applications
- Working with huge Warranty and Service Databases for an automotive company. Conduct data mining, text mining and advanced statistical analysis to provide early warning to customers related to their vehicle health and alerts for maintenance. Also, predict remaining useful life (RUL) of components such as battery, brakes, tyres, etc.to minimize maintenance cost.
- Develop analytical techniques and algorithms and technical software codes for the above.
- Corporate warranty and service system analyzers.
- Communicate results in research reports and oral presentations within the company.
Experience: 1- 15 Years
Education: PhD or Master in Statistics, Comp Science or Electrical Eng. Mathematics or equivalent
Mandatory Skill- All aspects of Text Mining, Data Mining, Signal processing, pattern recognition etc.
- Prognosis of structured and unstructured text. Ability to combine text mining with data mining for root cause analysis.
- Bayesian statistics, reliability modeling, robust statistics, solid statistical background with inclination towards industrial applications.
- Fast search algorithms development, ability to query from multiple databases and apply data mining, clustering and association rules for identifying patterns in the data.
- Statistics, combined with Operations research, and some background on econometrics. Multiple objective optimization techniques.
Remark: Any of the above mentioned skill is OK, depends on candidates years of experience
Customer Driven Advanced Vehicle Development Group (CDAVD)
Focus Area: Applied analytics, Stochastic Optimization & Stochastic Modeling, Human centred decision sciences, cognitive sciences, artificial intelligence. Demonstrated skillset in statistics, econometrics or applied operations research will be a plus. Exposure to industrial problem settings a big plus. Candidates should work in a self paced yet team based environment, working towards automotive new product development in general, and demand modeling/human centred decision sciences in particular.
Experience: 3+ Yrs mostly in Mathematics and not Statistics.
Education: PhD (preferable) or Masters
Contact: shama [at] peepalconsulting.com
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