Full Time
Posted 1 week ago

-Good with Machine Learning, well versed with python, its libraries and other analytical tools.
-Good knowledge of signal processing.
-Should be able to identify data sources and automate collection processes.
-Should be able to analyze a large amount of information to discover trends and patterns.
-Should be able to build predictive models and machine learning algorithms.
-Good knowledge and experience with Data Science and computer science.
-Can help in delivering advanced analytics in an enterprise environment.
-Collection, assembly, processing and visual representation of large datasets to describe patterns in agricultural productivity, the resilience of cropping systems and corresponding explanatory factors using data mining and machine learning.
-Ability to communicate complex ideas effectively, can help in structuring and solving problems and can conduct and interpret analysis independently.
Good experience with (big volume) data cleansing, handling and pruning.
-Complex Statistics understanding, statistical modeling, predictive analytics, machine learning and analytic approaches, inventing new algorithms.
-Strong data mining, programming and visualization skills.
-Data classification, regression, cluster analysis.
-Proficiency in computer programming and statistical computing (eg Python, R, MATLAB, and other Data Mining Tools).
-Demonstrated experience using machine learning with deep neural architectures to identify patterns in agriculture.

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