Key Responsibilities
R Application Development
- Design and develop R-based applications for data analysis and reporting
- Build and maintain interactive dashboards using RShiny and ShinyProxy
- Ensure scalability, performance, and usability of analytical applications
Data Analysis & Visualization
- Perform statistical analysis, data cleaning, transformation, and validation
- Create advanced visualizations using ggplot2 and other R libraries
- Generate actionable insights through exploratory data analysis
Big Data & Distributed Computing
- Work with Big Data frameworks such as Hadoop and Spark
- Process large-scale datasets for analytics and reporting use cases
- Optimize performance of data processing pipelines
Database & SQL Management
- Work with relational databases and write optimized SQL queries
- Ensure efficient data extraction, transformation, and loading processes
- Maintain data integrity and consistency across systems
Web Development Integration
- Use HTML, CSS, and JavaScript to enhance RShiny applications
- Improve UI/UX of analytical dashboards and reporting tools
- Ensure seamless integration between frontend and backend components
Machine Learning & Statistical Modeling
- Apply statistical techniques and machine learning methods to datasets
- Support predictive modeling and data mining initiatives
- Enhance analytical solutions using advanced algorithms
Collaboration & Requirement Gathering
- Work closely with business and technical stakeholders to understand requirements
- Translate business needs into technical solutions
- Communicate insights effectively to both technical and non-technical audiences
Code Quality & Optimization
- Optimize R code for performance and scalability
- Ensure adherence to coding standards and best practices
- Perform troubleshooting and debugging of applications
