R SHINY DEVELOPER (Remote position)

at Lantern Pharma

R SHINY DEVELOPER (Remote position)

Lantern Pharma

Company

Home

R SHINY DEVELOPER (Remote position)

at Lantern Pharma

Posted by Umesh Kathad

2 - 3 yrs

₹10L - ₹15L / yr

Remote only

Skills

R Programming

R Shiny

Data Visualization

Python

HTML/CSS

SQL

NOSQL Databases

Amazon Web Services (AWS)

Lantern Pharma is looking for talented and highly motivated R Shiny based front end web application developers to visualize the data analyzed / reports generated using bioinformatics pipelines. Leveraging your background and applying software engineering principles, to develop applications and tools in support of data visualization and reporting using R / R Shiny. You will be involved in generating complex graphs used for statistical analysis and interpretation using interactive libraries such as Plotly. In addition to development of new code, you will support and maintain standard R programs, which will comprise a library of code to be used for future development. This is a 6 months contract position (40 hrs / week) with possibilities of full time employment based on performance.

RESPONSIBILITIES:

Design and develop interactive web applications using R / R Shiny to visualize ML outputs, multi-omics data and reports generated by bioinformatics pipelines
Use the open-source or proprietary R libraries to build useful applications and packages
Write efficient, clean and well tested code that adheres to best practices
Organize data, analysis, reports, and applications into reproducible pipelines
Test and debug applications to ensure they are working correctly, using both manual and automated testing techniques
Stay up-to-date with the latest R packages and developments in the pharma industry
Publish R packages to internal company repository
Deploy and maintain the R Shiny web-application on the AWS server

BASIC QUALIFICATIONS:

Bachelor's degree required (Master’s degree preferred) in a scientific discipline such as Statistics, Computer Science, Bioinformatics etc.
Minimum 2 years of R / R Shiny, R Markdown experience with standard packages for data visualization and analysis
Proven ability of building interactive R-shiny application (demo of the R-shiny application)
Proficient in libraries such as ggplot2, plotly, dplyr, Highcharter and DT
Must have experience in generating and working with R markdown reports
Experience of AWS to host R shiny application is a plus
Knowledge of cancer biology, genomics and drug development is a plus
Familiarity with JavaScript, HTML, CSS, Python a plus
Experience in building a database using Relational / Non relational Database (SQL / NoSQL)
Must be capable of developing collaborative relationships with colleagues
Must be self-motivated and have strong analytical, interpersonal, and project management skills
Must demonstrate the ability to present ideas, issues, and observations in a clear manner

Lantern provides multiple growth opportunities and as an early team member, your work will have a direct impact on precision oncology that can transform drug development. In addition to attractive compensation, we offer employees the opportunity for competitive health, dental & vision insurance, stock options in a public company, an opportunity to take leadership on new and meaningful projects, & involvement with leading conferences & industry trade shows.

RESPONSIBILITIES:

Design and develop interactive web applications using R / R Shiny to visualize ML outputs, multi-omics data and reports generated by bioinformatics pipelines
Use the open-source or proprietary R libraries to build useful applications and packages
Write efficient, clean and well tested code that adheres to best practices
Organize data, analysis, reports, and applications into reproducible pipelines
Test and debug applications to ensure they are working correctly, using both manual and automated testing techniques
Stay up-to-date with the latest R packages and developments in the pharma industry
Publish R packages to internal company repository
Deploy and maintain the R Shiny web-application on the AWS server

BASIC QUALIFICATIONS:

Bachelor's degree required (Master’s degree preferred) in a scientific discipline such as Statistics, Computer Science, Bioinformatics etc.
Minimum 2 years of R / R Shiny, R Markdown experience with standard packages for data visualization and analysis
Proven ability of building interactive R-shiny application (demo of the R-shiny application)
Proficient in libraries such as ggplot2, plotly, dplyr, Highcharter and DT
Must have experience in generating and working with R markdown reports
Experience of AWS to host R shiny application is a plus
Knowledge of cancer biology, genomics and drug development is a plus
Familiarity with JavaScript, HTML, CSS, Python a plus
Experience in building a database using Relational / Non relational Database (SQL / NoSQL)
Must be capable of developing collaborative relationships with colleagues
Must be self-motivated and have strong analytical, interpersonal, and project management skills
Must demonstrate the ability to present ideas, issues, and observations in a clear manner

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About Lantern Pharma

Founded :

2014

Type :

Products & Services

Size :

20-100

Stage :

Raised funding

About

Lantern Pharma, Inc. is a clinical stage pharmaceutical company developing new classes of precision cancer drugs with novel mechanisms of action, and also rescuing or revitalizing abandoned or failed cancer drugs using machine learning techniques, genomic data and precision oncology trials. Lantern Pharma recognizes that the high cost and low success rates in oncology drug development largely stem from the inability to appropriately stratify patient populations prior to enrollment, and also from the inability to fully elucidate mechanisms of action that can suggest potent combinations. Our approach which leverages our RADR platform helps to provide rapid, meaningful insight to both of these central problems in oncology. Lantern is focused on accelerating personalized cancer therapy development through the use of AI and genomic-based patient stratification.

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