Senior Scientist - siRNA Off-Target Analysis
Role details
Job location
Tech stack
Job description
- Building, running, and improving scalable end-to-end computational transcriptomics assessment workflows (e.g., siRNA off-target assessment), from study intake through deliverables
- Applying transcriptomics, proteomics, biology, and fit-for-purpose statistics to identify, interpret, and clearly communicate signals and potential risk, in collaboration with TSRS Project Team Representatives
- Producing rigorous, traceable weight-of-evidence outputs (e.g., slide decks, technical summaries, and reports for regulatory submissions
- Developing and maintaining reusable computational tools and scripts in Python and R to support analysis, visualization, automation, and reporting
- Partnering closely with toxicologists, data scientists, in vitro scientists, oligonucleotide scientists, and cross-functional teams to refine analytical approaches and translate results into actionable biological insights
- Enabling reliable FAIR-aligned data/metadata flow and reproducible execution across workflows into the enterprise data fabric
- Evaluating and, where appropriate, applying AI-enabled approaches (including LLM-assisted or agentic tools) to improve analytical efficiency, consistency, and knowledge capture
Requirements
Doctorate degree PhD, Masters degree and 3 years of experience in computational biology, bioinformatics, data science, or related discipline, Bachelors degree and 5 years of experience in computational biology, bioinformatics, data science, or related discipline, * Experience supporting off-target analysis, risk assessment, or mechanistic interpretation for oligonucleotide, siRNA, or related therapeutic modalities
- Strong background in computational biology and transcriptomic data analysis in a research or drug discovery environment
- Demonstrated expertise in the analysis and interpretation of bulk RNA-seq data
- Experience with single-cell RNA-seq and proteomics analysis and interpretation
- Strong understanding of molecular and cellular biology, with the ability to translate transcriptomic findings into biologically meaningful insights
- Experience working with nonclinical safety data and familiarity with the role of toxicology in drug-development
- Strong programming expertise in Python and R, with experience developing reproducible computational workflows and analysis pipelines
- Experience applying basic statistical methods to biological datasets for analysis, interpretation, and decision support
- Experience preparing clear scientific reports and presentations for cross-functional teams and drafting regulatory documents
- Experience managing analytical data flow and implementing FAIR data principles and reproducible research practices
- Ability to work independently, manage multiple priorities, and contribute effectively in a cross-functional team environment
- Excellent communication and presentation skills, with the ability to convey complex computational and biological concepts to diverse audiences
- Experience evaluating or developing AI-enabled scientific workflows, including LLM-assisted analyses or agentic tools
Benefits & conditions
The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications.
In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include:
- A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
- A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible. Refer to the Work Location Type in the job posting to see if this applies.