Senior Scientist, siRNA Design and Off-Target Analysis

AbbVie

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Worcester, MA
Salary: $109,500–$208,500 / yr
Posted: 25 days ago
Freshness: Confirmed live yesterday
Closes: Aug 17, 2126
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k

This role $159k

$93k most similar roles pay here $263k

This role pays less than 78% of similar roles. Most pay $162,000–$246,534 — the shaded band above. At the midpoint, this role pays about $159k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About AbbVie

AbbVie is a global biopharmaceutical company focused on discovering and delivering innovative medicines and solutions in immunology, oncology, neuroscience, and eye care. Its products include Humira, Skyrizi, and Rinvoq.

AbbVie currently has 297 open roles on FindRole.

Listed pay typically runs $109,500–$208,500 across 271 roles with salary data.

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At a glance

TL;DR · Senior Scientist, siRNA Design and Off-Target Analysis

Role Posting Log in to save

Senior Scientist, siRNA Design and Off-Target Analysis joins the Biotherapeutic and Genetic Medicine department to support siRNA design and off-target assessment. The role involves establishing and optimizing siRNA sequences for enhanced knockdown efficacy while reducing off-target liabilities. Key responsibilities include building machine learning models based on high-throughput screening data, developing off-target assessment workflows, and integrating transcriptomic and genomic data. The candidate will develop version-controlled tools and pipelines using Python or R to automate analysis and reporting. They will collaborate with internal teams on NGS library preparation and translate findings into actionable biological insights for RNA-based therapeutics. Required skills include proficiency in Python and R, experience with transcriptomic data analysis, and a strong background in molecular biology. The role focuses on solving technical challenges related to nonclinical safety assessment and improving the selectivity of siRNA and other nucleic acid modalities.

Skills

Python R Machine Learning Transcriptomics Genomics RNAi siRNA Multi-omics version-control Cellular Biology LLM Automation

What you'll do

Develop and optimize pipelines for siRNA sequence design using genomic, transcriptomic, and RNA structural data.
Build machine learning models based on high-throughput screening data to improve siRNA selection.
Interpret transcriptomic data to identify potential off-target signals and biological risks.
Create and maintain version-controlled tools and scripts in Python or R for analysis and automation.
Support NGS library preparation and validation studies for seed-mediated and sequence-dependent off-target effects.
Translate complex data into actionable biological insights for cross-functional partners.
Produce clear, traceable data analysis reports, slide decks, and technical summaries.

What we're looking for

BS, MS, or PhD in computational biology, genomics, RNA biology, or a related field.
0-4+ years experience for PhD holders, 8-10+ years for MS holders, or 10-12+ years for BS holders.
Proficiency in Python and/or R to develop reproducible analytical workflows and pipelines.
Experience supporting off-target analysis, mechanistic interpretation, or risk assessment for siRNA, ASO, or related modalities.
Strong background in NGS library preparation technologies and transcriptomic data analysis.
Ability to translate transcriptomic findings into biologically meaningful conclusions based on molecular and cellular biology knowledge.
Experience preparing scientific reports, presentations, or regulatory-facing documentation.
Experience with multi-omics integration, RNAi mechanisms, or machine learning-enabled workflows (preferred).

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