Scientist III

Boehringer Ingelheim; Ridgefield (CT); On-site; USD 90,000 - 140,000; Full time

Job summary

Boehringer Ingelheim is hiring a bioscience data analyst to design and deploy NGS data analysis workflows and to integrate multi-omics data for drug discovery in a collaborative environment.

The role emphasizes interpreting omics data (bulk RNA-seq, scRNA-seq, ATAC-Seq), developing visualizations with R Shiny and D3, and applying novel methods while maintaining data integrity.

Qualifications

• Strong scientific understanding and experience in bioinformatics.
• Experience in pharmaceutical research is a plus.
• Ability to design and deploy NGS data analysis workflows for processing, visualization, integration and mining.
• Experience interpreting bulk RNA-seq, scRNA-seq and ATAC-Seq data.
• Fluent with modern data visualization methods (R Shiny, D3).
• Knowledge of multi-omics integration for drug discovery targets.

Responsibilities

• Design, implement and/or deploy NGS data analysis workflows for data processing, visualization, integration and mining.
• Analyze omics data sets and interpret genomic data (bulk RNA-seq, scRNA-seq, ATAC-Seq).
• Develop data visualization using R Shiny and D3.
• Integrate diverse datasets to identify drug targets and biomarkers.
• Benchmark methods, QC measures, and apply innovative analysis approaches.
• Present results to colleagues and collaborators.

Skills

Bioinformatics

NGS data analysis

Multi-omics integration

Data visualization

R

Python

Shiny

UNIX/Linux

Nextflow

Bioconductor

Cloud computing

Education

Master’s degree in Computer Science, Genomics, Biostatistics or Bioinformatics

Bachelor’s degree with 7+ years in STEM

Tools

R

Python

Shiny

UNIX/Linux

Nextflow

Cloud platforms

Bioconductor

Job description

Strong scientific understanding and experience in bioinformatics

Experience in pharmaceutical research a plus

Design, implement and/or deploy NGS data analysis workflows for data processing, visualization, integration and mining to support novel therapeutic target identification and disease biomarker discovery

Data Analysis : Implement methods for omics data analysis, and interpretation of genomic data sets (e.g., bulk RNA-seq, scRNA-seq, ATAC-Seq)

Data Visualization: Fluency in contemporary data visualization methods like R Shiny , D3

Data Integration: Analyzing diverse datasets (multi-omics) to find relevant drug discovery targets and downstream effects relevant to immune disease

Data Mining: Internal, collaborative, and public databases to assist in the characterization of immune disease

Select and benchmark methods and tools, define and perform appropriate QC measures

Apply and develop innovative analysis approaches when standard methods are not adequate

Interpret and present analysis results to coworkers and collaborators

Follow relevant scientific literature to ensure use of optimal methods and understand emerging practices across the field

Demonstrates the ability to interpret the outcome of experiments, propose appropriate follow-up, and may propose new avenues of investigation

Communicates own work effectively orally and in writing; contributes to writing protocols, procedures, and technical reports

Automate processing and results reporting and delivery

Reports and treats data with a high level of integrity and ethics

Complies with applicable regulations; Maintains proper records in accordance with SOPs and policies

The successful candidate will have experience with more than one of the following; analyzing next-generation sequencing (NGS), functional genomics, statistics for big data analysis, or multi-omics data integration

Good knowledge of existing bioinformatics databases and file formats

In-depth understanding of computational methods for NGS analysis and the usage of public data resources required

Strong hands‑on skills in relevant programming languages (e.g., R, Python, Shiny, UNIX/Linux, UNIX bash shell scripting, Nextflow), statistical software, cloud computing, visualization tools, and relevant R/Bioconductor packages

Demonstrated ability to produce well‑designed and documented code

Familiarity with computational biology tools and experience working with computational biologists to solve problems

Must enjoy working in a multi‑disciplinary and collaborative environment

Ability to troubleshoot both individually and as part of a team

Excellent oral and written skills with the ability to communicate in an open, transparent, timely and consistent manner

Master’s degree from an accredited institution with one-plus (1+) years of experience in a related scientific discipline (Computer Science, Genomics, Biostatistics or Bioinformatics preferred) OR Bachelor’s degree from an accredited institution with seven-plus (7+) years of experience in a STEM discipline.