General Mills off- campus recruitment drive to hire candidates  for Analyst – Analytics. Interested candidate can read the  details and apply as soon as possible.

About: General Mills is an American multinational manufacturer and marketer of branded consumer foods sold through retail stores. It is headquartered in Golden Valley, Minnesota, a suburb of Minneapolis. Often nicknamed “Big G”, the company markets many well-known North American brands, including Gold Medal flour, Annie’s Homegrown, Betty Crocker, Yoplait, Colombo, Totino’s, Pillsbury, Old El Paso, Häagen-Dazs, Cheerios, Trix, Cocoa Puffs, and Lucky Charms. Its brand portfolio includes more than 89 other leading U.S. brands and numerous category leaders around the world.

Position: Analyst – Analytics

Location: Mumbai

Post resume: SetNaukri.com

Experience: 0-2 years

Eligibility:

  • Bachelors/Masters degree.
  • Preferred Professional Certifications: Data Analytics, Machine learning.

Job Responsibilities:

  • Generate forecast for New Items using like item modelling approach.
  • Collect data from multiple system using SQL/PLSQL.
  • Pre-process Data – Outlier detection/removal, Univariate, multivariate, robust regression, data smoothening.
  • Identify Pattern in data- Trend, Seasonality and noise decomposition.
  • Perform descriptive & diagnostics analysis on historical demand & shipment data.
  • Build statistical models using historical demand data.
  • Cluster & Classify data using different machine learning methods.
  • Forecast Visual analytics, scenario planning, model diagnostics.
  • Regression methods- Correlation, ANOVA, Chi squared, Dimensionality reduction, squared, adjusted r squared, p value, composite models.

Skills:

  • Good understanding of Demand Planning and supply planning processes.
  • Hands on experience on machine learning – various types of regression, classification and clustering techiques.
  • R and/or PYTHON Programming.
  • SQL/PLSQL.
  • Data visualization using Excel and/or Tableau.
  • Pivoting, conditional data formatting, charts, graphs.
  • Handling large data sets in various formats, volume and dimensions.
  • Fundamentals of linear algebra,matrices and probability.

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