Mid Level Computational Scientist Jobs
Mid level computational scientist jobs go to researchers and engineers ready to own simulation pipelines, lead analytical workstreams, and drive methodological decisions with limited oversight. Hiring runs across Biotechnology & Pharmaceuticals, Education, and Science & Research, with 33% of openings listed as remote or hybrid, and employers like dsm-firmenich, Sail Biomedicines, and Cogent Biosciences competing for talent at this level now.
Find JobsOverview
Showing 5 of 5+ Mid Level Computational Scientist jobs
Looking for more mid level computational scientist jobs?
Explore related role searches to find more openings that fit.
See related jobsThe Position
Join our team and drive the future of programmable eRNATM therapeutics and In Vivo CAR-T therapies where artificial intelligence, targeted delivery systems and next-generation immunotherapy converge to redefine what’s possible for patients. As a key member of the Sail Biomedicines Computational Biology team, the Senior Scientist I will operate at the interface of platform and program, applying data-driven approaches to champion broad platform efforts and hands-on analysis of preclinical datasets to transform the treatment landscape for autoimmune diseases, and beyond. The ideal candidate brings a strong foundation in computational biology and a record of independently developing, implementing, and critically evaluating computational methods for biological research. They should be comfortable reasoning through methodological assumptions, limitations, and biological implications of an analysis, from raw measurements through interpretation. The role will directly support In Vivo CAR-T immunology programs and platform development, with opportunities to contribute to building capabilities spanning molecular and systems modeling, computational protein design, and AI-based therapeutic engineering.
Responsibilities
- Lead analysis of preclinical research datasets, including immunophenotyping, functional assays, and multi-omics data to support therapeutic development
- Develop, adapt, and benchmark computational and statistical methods to address biological questions where standard workflows are insufficient
- Integrate and interpret data across studies leveraging internal and external resources to contextualize findings, evaluate consistency, and strengthen understanding of our therapeutics
- Partner with experimental scientists to shape experimental design, identify limitations, interpret results, and prioritize follow-up studies
- Build and maintain reproducible analysis workflows, with clear documentation and version control (Git) with consistent data annotation and metadata practices
- Communicate findings, uncertainty, and implications with collaborators through effective visualizations, presentations, and written summaries
Qualifications
Required:
- Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics, or a related quantitative discipline
- 3+ years of hands-on computational biology research in biotech, pharma, or academia
- A record of independently leading substantial computational biology projects, including developing, adapting, and benchmarking analytical methods. Evidence may include methods development, reusable scientific software, publications, or documented contributions to therapeutic research
- Deep expertise in at least one relevant area, such as transcriptomics, multi-omics analysis, or quantitative analysis of preclinical studies, spanning data generation, quality control, methodological choices, and biological interpretation
- Strong grounding in statistical modeling, with demonstrated ability to address confounding, batch effects, biological versus technical variation, and experimental-design limitations, and to assess uncertainty and sensitivity to analytical choices
- Strong programming skills in Python and/or R, with experience independently developing and maintaining reproducible, well-documented scientific analysis code and workflows
- Demonstrated ability to collaborate effectively with experimental scientists, take ownership of scientific questions, be a proactive force driving improvement, and be comfortable developing to contribute beyond your core area of expertise
Preferred:
- Experience in CAR biology, immunology, cell therapy, or RNA therapeutics
- Experience integrating heterogeneous datasets across studies or conducting meta-analysis
- Experience with workflow orchestration tools to cloud-based or collaborative data environments
- Track record of impactful scientific contributions (publications or program support)
- Computational protein design and/or structural biology experience a plus
About Sail Biomedicines
Sail Biomedicines is building a new class of fully programmable medicines by integrating circular RNA (eRNA™), targeted nanoparticle delivery, and advanced computational approaches. Our platform enables the systematic design and optimization of therapies, unlocking new possibilities across immunology and beyond.
Salary Range: $130,000 - $170,000
Sail Biomedicines is an Equal Opportunity Employer. Sail does not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, veteran status, or any other status protected under federal, state, or local law.
The Position
Join our team and drive the future of programmable eRNATM therapeutics and In Vivo CAR-T therapies where artificial intelligence, targeted delivery systems and next-generation immunotherapy converge to redefine what’s possible for patients. As a key member of the Sail Biomedicines Computational Biology team, the Senior Scientist I will operate at the interface of platform and program, applying data-driven approaches to champion broad platform efforts and hands-on analysis of preclinical datasets to transform the treatment landscape for autoimmune diseases, and beyond. The ideal candidate brings a strong foundation in computational biology and a record of independently developing, implementing, and critically evaluating computational methods for biological research. They should be comfortable reasoning through methodological assumptions, limitations, and biological implications of an analysis, from raw measurements through interpretation. The role will directly support In Vivo CAR-T immunology programs and platform development, with opportunities to contribute to building capabilities spanning molecular and systems modeling, computational protein design, and AI-based therapeutic engineering.
Responsibilities
- Lead analysis of preclinical research datasets, including immunophenotyping, functional assays, and multi-omics data to support therapeutic development
- Develop, adapt, and benchmark computational and statistical methods to address biological questions where standard workflows are insufficient
- Integrate and interpret data across studies leveraging internal and external resources to contextualize findings, evaluate consistency, and strengthen understanding of our therapeutics
- Partner with experimental scientists to shape experimental design, identify limitations, interpret results, and prioritize follow-up studies
- Build and maintain reproducible analysis workflows, with clear documentation and version control (Git) with consistent data annotation and metadata practices
- Communicate findings, uncertainty, and implications with collaborators through effective visualizations, presentations, and written summaries
Qualifications
Required:
- Ph.D. in Computational Biology, Bioinformatics, Systems Biology, Biophysics, or a related quantitative discipline
- 3+ years of hands-on computational biology research in biotech, pharma, or academia
- A record of independently leading substantial computational biology projects, including developing, adapting, and benchmarking analytical methods. Evidence may include methods development, reusable scientific software, publications, or documented contributions to therapeutic research
- Deep expertise in at least one relevant area, such as transcriptomics, multi-omics analysis, or quantitative analysis of preclinical studies, spanning data generation, quality control, methodological choices, and biological interpretation
- Strong grounding in statistical modeling, with demonstrated ability to address confounding, batch effects, biological versus technical variation, and experimental-design limitations, and to assess uncertainty and sensitivity to analytical choices
- Strong programming skills in Python and/or R, with experience independently developing and maintaining reproducible, well-documented scientific analysis code and workflows
- Demonstrated ability to collaborate effectively with experimental scientists, take ownership of scientific questions, be a proactive force driving improvement, and be comfortable developing to contribute beyond your core area of expertise
Preferred:
- Experience in CAR biology, immunology, cell therapy, or RNA therapeutics
- Experience integrating heterogeneous datasets across studies or conducting meta-analysis
- Experience with workflow orchestration tools to cloud-based or collaborative data environments
- Track record of impactful scientific contributions (publications or program support)
- Computational protein design and/or structural biology experience a plus
About Sail Biomedicines
Sail Biomedicines is building a new class of fully programmable medicines by integrating circular RNA (eRNA™), targeted nanoparticle delivery, and advanced computational approaches. Our platform enables the systematic design and optimization of therapies, unlocking new possibilities across immunology and beyond.
Salary Range: $130,000 - $170,000
Sail Biomedicines is an Equal Opportunity Employer. Sail does not discriminate based on race, religion, color, sex, gender identity, sexual orientation, age, national origin, veteran status, or any other status protected under federal, state, or local law.
See All 5 Mid Level Computational Scientist Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsMid Level Computational Scientist Job Market
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Education
- Science & Research
- Chemicals & Materials
Mid Level Computational Scientist Jobs: Frequently Asked Questions
How do I get a mid level computational scientist job?
Position yourself around ownership, not just contribution. Highlight projects where you designed the approach, debugged the model, and delivered results independently. Tailor your application to show domain depth, whether that is molecular dynamics, fluid simulation, or data-intensive scientific computing. Demonstrating that you can work across research and engineering teams, and communicate findings to non-specialists, sets mid level candidates apart from recent graduates.
Which companies hire mid level computational scientists?
Companies hiring mid level computational scientists right now include dsm-firmenich, Sail Biomedicines, and Cogent Biosciences, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a mix of national research-driven enterprises, technology companies with scientific computing divisions, and specialized engineering firms that need scientists who can operate independently on complex modeling work.
Are there remote mid level computational scientist jobs?
Yes, though availability varies by industry and project requirements. About 33% of mid level computational scientist openings are remote or hybrid as of November 2026, reflecting strong demand from employers who prioritize modeling and simulation work that can run on cloud or remote clusters. Roles tied to lab instrumentation or on-site high-performance computing systems are more likely to require in-person presence.
How do I move up to a mid level computational scientist role?
Moving into a mid level role is about accumulating depth and demonstrated ownership over your early career. Build expertise in one or two computational methods, contribute to projects from design through delivery, and seek out work where you are accountable for outcomes, not just tasks. Presenting peer-reviewed work, open-source contributions, or documented performance improvements on real systems shows the progression evaluators look for when promoting from junior to mid level.
Which industries hire the most mid level computational scientists?
Mid Level computational scientist roles concentrate in Biotechnology & Pharmaceuticals, Education, and Science & Research, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because their core workflows, from drug discovery to aerospace modeling to financial risk simulation, depend on scientists who can independently build, validate, and iterate on computationally intensive models without close supervision.