Profile - R Shiny Engineer

Experience: 3 to 8 years

Location - MN Delhi

Budget 14 to 16 LPA

Key Responsibilities:

1. R Shiny Application Development: Design, develop, and maintain interactive web

applications using R Shiny to visualize and analyse data in an engaging and user-friendly

manner.

2. Data Visualization: Create visually appealing and informative data visualizations, charts, and

dashboards to effectively communicate complex insights to stakeholders.

3. Data Manipulation and Analysis: Utilize your expertise in data science to manipulate, clean,

and analyse large datasets, extract meaningful patterns, and generate actionable insights.

4. Statistical Analysis: Apply statistical methods and models to uncover trends, correlations,

and patterns within the data, supporting data-driven decision-making processes.

5. Collaboration: Work closely with data scientists, analysts, and other stakeholders to

understand business requirements and translate them into functional R Shiny applications.

6. Performance Optimization: Continuously optimize application performance to ensure

efficient processing and responsiveness.

7. Documentation: Create clear and concise documentation for developed applications,

including user guides and technical specifications.

8. Quality Assurance: Conduct thorough testing to identify and resolve bugs, ensuring the

reliability and accuracy of the developed applications.

9. Data Integration: Integrate R Shiny applications with various data sources and databases,

ensuring seamless data flow and real-time updates.

10. Stay Updated: Keep abreast of the latest developments in R Shiny, data science, and related

technologies, and share knowledge and insights with the team.

Qualifications:

1. Bachelor's or masters degree in Computer Science, Data Science, Statistics, or a related

field.

2. Proven experience (3-8 years) in developing interactive web applications using R Shiny.

Must Technical Skills:

1. Strong proficiency in R programming, data manipulation packages (e.g., dplyr, tidyr), and

data visualization libraries (e.g., ggplot2, plotly).

2. Solid understanding of data science concepts, statistical analysis, and machine learning

algorithms.

3. Experience with data visualization best practices and the ability to create insightful and

compelling visual representations of data.

4. Familiarity with data querying languages (e.g., SQL) and database management.

5. Knowledge of version control systems (e.g., Git) and collaborative development practices.

6. Excellent problem-solving skills and the ability to analyze and interpret complex datasets.

7. Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform

(Optional)

8. Familiarity with PowerPoint would be handy

Soft Skills

1. Excellent communication and collaboration skills to effectively convey technical concepts to

technical and non-technical stakeholders.

2. Understanding agile development methodologies and experience working in an agile team

environment.

3. Demonstrate the candidate's versatility and adaptability to new challenges.

4. A self-starter who enjoys working in a fast-paced, dynamic environment

5. A passion for staying up-to-date with emerging technologies and a drive to continuously

learn and improve.

Please share your CV on(e-mail removed)orapply here.