Primary Skills (Must-have)
Writing reusable, testable, and efficient codes
Good Understanding of Datatypes (numeric, integer, character, factor, boolean etc.) & Data Structures (Vector, Array, Matrix, Dataframe, List etc.),Inter-Conversion between these data structures.
File IO & File Formats (Reading and Writing txt, csv, excel, psv, rds & rda files)
Conditional & Iterative control statements & Handling of date values in R.
Functions (User Defined & Built-in functions),Apply functions & Operators (Logical, Relational & Special Operators)
Sub setting using indices, names, Boolean values on different data structures.
Variable Scoping & Environments (Global & Local Environments)
Data Wrangling (Joins, Sorting, searching etc.) & Manipulation of Data frames (Addition / Deletion of rows & columns, Filtering, Grouping, Summarizing etc.)
Good knowledge of common data processing packages like dplyr, tidyr, lubridate, purr, data.table etc.
Visualization (Using base-R, ggplot, plotly etc.)
R-Packaging, Versioning
Building dashboards using frameworks like Shiny
Basic unix/linux commands
Secondary Skills (Good-to have)
Object Oriented Programming (Classes & Objects)
REST API using Plumber & Rest RServe
Knowledge of RHadoop, ORCH, RHIPE, Hadoop Streaming etc. and processing of large data sets in R
Knowledge of using TensorFlow, Keras, PyTorch from R
Knowledge of ODBC package within R
Experience of Angular or React frameworks
Experience:2-3 years of experience of working as a R programmer
Working knowledge of R libraries used for Data Analytics and Machine Learning
Building data pipelines in R
Manipulating large data sets using R
Creating REST APIs and Shiny applications using R
Creating visualization using R
Experience of production deployment
Experience of unit testing and integration testing