Job Description:

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  The ideal candidate would be adept at understanding customer's business challenges and define appropriate analytics approach to design solution

  
  


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  Should be able to convert mathematical/ statistics-based research/ academic literature into sustainable data science solutions

  
  


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  This is a hands-on role, will be required to manage day to day delivery activities and guide team in executing analytics projects by analysing large volume of data

  
  


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  Research and bring innovations to develop next generation solutions in core functional areas related to Promotion Effectiveness, Forecasting with detrending methods, Digital Marketing, Customer Relationship Management (CRM), Campaign Management & Data Insights etc.

  
  


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  Provide technical thought leadership, coaching and mentorship in the field of data science in working with engineering and other cross functional teams

  
  


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  Evolve the approach for the application of machine learning/deep learning to existing program and project disciplines

  
  


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  He / She would also be responsible for creating Business & technical presentations, reports etc. to present the analysis findings to the end clients and for business development

  
  


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  This role requires excellent communication skills.

  
  

Qualifications

Educational Criteria:

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  Masters in Statistics/Mathematics/Economics/Econometrics from Tier 1 institutions Or

  
  


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  Bachelor of Engineering or MBA from Tier 1 institutions – Preferred

  
  

Additional information

Technical Experience: (not all technical exposures are expected from one individual)

Must Have:

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  Clustering, Decision Tree, Random Forest, Support Vector Machine, Naïve Bayes, GBM, XGBoost, Multiple linear regression, Logistic regression, ARIMA/ARIMAX

  
  


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  Tools: Python, SQL, Spark

  
  

Good to Have:   

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  Hands on experience in developing models (end to end)

  
  


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  Model automation, Bayesian Inference/simulators, Bayesian Filters, GLM (Generalised Linear Models), GMM (Gaussian Mix Models) etc

  
  


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  Recommended system (ALS, MF, Collaborative filtering and Content Filtering), Deep Learning methods

  
  


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  Optimization Method like BFGS, differential evolutionary, MOO (multi objective optimization) etc

  
  


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  Sound understanding of mathematics like probability theory, differential calculus, Laplace and Furrier transformations etc

  
  


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  Tools: TensorFlow, big data, Experience on AWS platforms, Knowledge of any visualization tools like Tableau, Quick sight, Qlik sense, Power BI etc. is a plus