Details:

We need ace data scientists who can develop best-in-class predictive models, machine learning models, and deep learning models and at the same time, they should be able to explain the decisions taken by the models automatically through plain simple English language. The explainable elements should not be limited to the numbers and formulas,  there must be a bit of personalization also to understand the context of the problem 

Min. Qualification:

• Bachelors in Computer Science/ Statistics/Econometrics/Applied Mathematics/Applied  Statistics/Operations Research is a must.
•  Must have hands-on experience: Pyspark, Kafka, Redshift, APIs, Flask, AWS, and  Docker. 
• Must have a minimum of 4+ years of industry experience in developing data science models. 
• Deep understanding and experience in the field of Statistical Modelling, Statistical  Analysis and Machine Learning 
• Must have thorough mathematical knowledge of correlation/causation, decision trees,  classification and regression models, recommenders, probability, and stochastic processes, distributions, priors, and posteriors. 
• Skilled at scientific programming languages such as Python, R, Matlab, and writing deployable code into production. 
• Familiarity with R, Apache Spark, and another scientific python/R modules is a must.

Skills Required:

Pyspark, Kafka, Redshift

Roles:

• Passion for learning new technologies and be up to date with the scientific research community. 
• Work in technical teams in the development, deployment, and application of machine learning solutions, leveraging technical components and explaining the modelling decisions.
• Take responsibility for insights, reports, and explainability of the decisions taken by predictive models.
• Responsible for taking an idea from concept to production thoroughly with feedback from all stakeholders.