JD :
Candidate should be:
- The ideal candidate will come with hands-on experience as a Data Scientist having a Data-oriented personality with a good scripting and programming skills.
- He/she should have hands-on expertise on data science toolkits, specifically in using R for statistical modeling and machine learning.
- Expert level understanding of machine learning algorithms (regression/classification/ naïve Bayer/ Decision Trees/ Random Forest) and their real-world advantages/drawbacks along with performance metrices
- Demonstrated R and Shiny expertise (mandatory). Other programming languages like python are added advantages.
- Development and maintenance of Shiny R web applications as per client specifications
- If development / analysis skills are demonstrated on public platforms like Kaggle.com, git hub, R bloggers then it would be awesome.
- High level of accountability
R and Shiny Specific Skills:
- Knowledge of reactive programming, debugging and scaling in R Shiny
- Develop and help to design R based frameworks to compute advanced graphs, insights from data in form of interactive visualizations, tables and listings, generating reports using R markdown.
- R Shiny based modular framework for the interactive and reproducible exploration of clinical trials data.
- Ability to create intuitive visualizations using R packages such as ggplot, ggplot2, lattice, and plotly.
Expertise with R packages such as tidyverse, dplyr, maggrittr, stringr, purr, and tidyr
Preferred Experience
- Experience with GitHub, AWS
- Knowledge in metabolomics, signal processing, NMR spectroscopy
- Experience with SQL, Ruby, Matlab, Python
- Pharma or Life science domain Background is a Plus