Mu Sigma Off Campus Drive Hiring Freshers As Data Scientist For M.Sc Statistics/Applied Statistics/Maths /Applied Mathematics


About the Company: Mu Sigma is an Indian management consulting firm that primarily offers data analytics services. The firm’s name is derived from the statistical terms “Mu” and “Sigma” which symbolize the mean and the standard deviation respectively of a probability distribution

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Company name : Mu- Sigma

Job Role: Decision Scientist

Salary : Best in Industry

Eligibility: M.Sc Statistics/Applied Statistics/Maths /Applied Mathematics

Work Location : Bangalore

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Job Overview

  • The ideal candidate is adept at understanding business requirements, has the ability to break down the problem and able to identify the right mathematical techniques.
  • They must have strong understanding and intuition about different statistical and machine learning techniques, understand their pros and cons, and has experience of implementing these techniques.
  • They must be capable on a variety of problems. data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations.
  • They must have a proven ability to drive business results with their data-based insights.
Job Responsibilities
• Explore and evaluate different techniques that help solve the business problem at hand.
• Develop solutions that are a mix of
• Ensure reproducibility of experiments and
• Keep up to date with new technologies Qualifications for Data Scientist Must have:
• Strong problem-solving skills with an emphasis on product development.
• Knowledge of using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets.
• Knowledge of basic statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.)
• Excellent written and verbal communication skills for coordinating across teams.
• A drive to learn and master new technologies and techniques.
Good to have:
• Coding knowledge and experience with several languages: C, C++, Java, JavaScript, etc.
• Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
• Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.
• Creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, Gurobi, MySQL, etc