Job description

Date Posted:
Narsingpur, Kherki Daula Post, Delhi Jaipur Road, Gurgaon - 122004 (Haryana), India
  • Implement statistical methods to solve specific business problems utilizing code (Python, R, Scala, etc.)
  • Utilize code (Python, R, Scala, SQL etc.) for analyzing data and building statistical and machine learning models and algorithms
  • Improve upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters
  • Improve upon existing Demand Forecasting statistical or machine learning methodologies by developing new data sources, testing model enhancements, running computational experiments, and fine-tuning model parameters for new forecasting models
  • Directly contribute to the design and development of automated Demand forecasting systems
  • Build internal customer-facing reporting tools (using our Carrier AWS platform) to provide insights and metrics which track forecast performance and explain variance
  • Present critical data in a format that is immediately useful to answer questions about the inputs and outputs of Demand Forecasting systems and improving their performance
  • Communicate verbally and in writing to business customers with various levels of technical knowledge, educate them about forecast models, as well as sharing insights and recommendations
  • Support decision making by providing requirements to develop analytic capabilities, platforms, pipelines and metrics then using them to analyze trends and find root causes of forecast inaccuracy
  • Formalize assumptions about how demand forecasts are expected to behave, create definitions of outliers, develop methods to systematically identify these outliers, and explain why they are reasonable or identifying fixes for them
  • collaborate directly with software developers and data engineers part our Data Analytics COE to build end-to-end data pipelines and production code
Carrier is An Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class.
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