Scientist III, Data Scientist, Bioprocess Digital Twin
Grand Island, New York, United States of America
- Pay
$89,000–149,800/yearAnnual period assumed · Location-specific pay — pay source
Compensation and Benefits The salary range estimated for this position based in New York is $89,000.00–$149,800.00. This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingBuild, test, and evaluate models of nutrient use, metabolites, cell growth, viability and productivity
Analyze time-series bioreactor, assay, spent media and process metadata
Use Python to process data, run simulations and visualize results
Summarize modeling results and document assumptions for scientists and engineers
From the employer’s posting
Build, test, and evaluate models for key upstream process behaviors, including nutrient consumption, metabolite accumulation, cell growth, viability, and productivity.
Analyze bioprocess datasets, including time-series bioreactor data, offline assay results, spent media data, and process metadata.
Use Python and scientific computing tools to process data, run simulations, visualize results, and support model evaluation.
Collaborate with scientists, engineers, and software developers to summarize modeling results, document assumptions, and support experimental planning.
What you’ll bring
All qualificationsCore experience
- Master's or Ph.D’s Degree in Biochemical Engineering, Chemical Engineering, Biotechnology, Computational Biology, Systems Biology, Bioinformatics, Cell Biology, or a related field.
- Good understanding of CHO cell culture and upstream bioprocessing concepts, including media, feeding strategies, bioreactor operation, metabolites, cell growth, viability, productivity, and process parameters.
- Hands-on Python experience for scientific computing, data analysis, visualization, simulation, or model implementation.
- Experience working with bioprocess or biological datasets, especially time-series data, assay results, spent media data, or process metadata.
- Familiarity with mechanistic, statistical, machine learning, or hybrid modeling approaches for biological or process systems.
- Ability to work effectively in cross-functional teams and contribute to project activities under guidance from senior scientists or project leads.
Preferred experience
- Familiarity with PAT systems, bioreactor data infrastructure, LIMS/ELN/MES environments, cloud-based data workflows, or software-enabled scientific tools is a plus.
Qualification wording
Master's or Ph.D’s Degree in Biochemical Engineering, Chemical Engineering, Biotechnology, Computational Biology, Systems Biology, Bioinformatics, Cell Biology, or a related field.
Good understanding of CHO cell culture and upstream bioprocessing concepts, including media, feeding strategies, bioreactor operation, metabolites, cell growth, viability, productivity, and process parameters.
Hands-on Python experience for scientific computing, data analysis, visualization, simulation, or model implementation.
Experience working with bioprocess or biological datasets, especially time-series data, assay results, spent media data, or process metadata.
Familiarity with mechanistic, statistical, machine learning, or hybrid modeling approaches for biological or process systems.
Ability to work effectively in cross-functional teams and contribute to project activities under guidance from senior scientists or project leads.
Familiarity with PAT systems, bioreactor data infrastructure, LIMS/ELN/MES environments, cloud-based data workflows, or software-enabled scientific tools is a plus.
Education & alternatives
Education - Master's or Ph.D’s Degree in Biochemical Engineering, Chemical Engineering, Biotechnology, Computational Biology, Systems Biology, Bioinformatics, Cell Biology, or a related field. Qualifications & Experience
Tools in this posting
- Python
Source — Tool mentions in context
- Analyze bioprocess datasets, including time-series bioreactor data, offline assay results, spent media data, and process metadata. - Use Python and scientific computing tools to process data, run simulations, visualize results, and support model evaluation. - Collaborate with scientists, engineers, and software developers to summarize modeling results, document assumptions, and support experimental planning.
- Good understanding of CHO cell culture and upstream bioprocessing concepts, including media, feeding strategies, bioreactor operation, metabolites, cell growth, viability, productivity, and process parameters. - Hands-on Python experience for scientific computing, data analysis, visualization, simulation, or model implementation. - Experience working with bioprocess or biological datasets, especially time-series data, assay results, spent media data, or process metadata.
Benefits in the posting
Full benefits wording- This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:
- A choice of national medical and dental plans, and a national vision plan, including health incentive programs
- Employee assistance and family support programs, including commuter benefits and tuition reimbursement
- At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
- Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
- Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount
From the employer’s posting.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 12, 2026 · 17 days ago
- Recorded sightings
- 14
- Last seen by us
- Oct 29, 2026
- Reposted
- once since Jul 1, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications. We count a repost when the same title and location comes back as a new listing within 60 days of the last one coming down. Some hiring systems expire listings on a schedule, so repost rates vary by system.
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- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job description
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer.
DESCRIPTION:
Join our team at Thermo Fisher Scientific as a Data Scientist III and contribute to global healthcare and scientific innovation. You'll apply advanced analytics, machine learning, and AI techniques to solve complex business challenges across our enterprise. In our collaborative environment, you'll develop and deploy sophisticated data science solutions that drive operational efficiencies and enhance decision-making capabilities. This role offers the opportunity to work with advanced technologies while contributing to our mission of enabling customers to make the world healthier, cleaner, and safer.
Responsibilities
- Support development of predictive modeling and simulation workflows for CHO cell culture and upstream bioprocess digital twin applications.
- Build, test, and evaluate models for key upstream process behaviors, including nutrient consumption, metabolite accumulation, cell growth, viability, and productivity.
- Analyze bioprocess datasets, including time-series bioreactor data, offline assay results, spent media data, and process metadata.
- Use Python and scientific computing tools to process data, run simulations, visualize results, and support model evaluation.
- Collaborate with scientists, engineers, and software developers to summarize modeling results, document assumptions, and support experimental planning.
Education
- Master's or Ph.D’s Degree in Biochemical Engineering, Chemical Engineering, Biotechnology, Computational Biology, Systems Biology, Bioinformatics, Cell Biology, or a related field.
Qualifications & Experience
- Relevant academic or industry experience in upstream bioprocessing, cell culture, process modeling, computational biology, data science, or related scientific domains.
- Good understanding of CHO cell culture and upstream bioprocessing concepts, including media, feeding strategies, bioreactor operation, metabolites, cell growth, viability, productivity, and process parameters.
- Hands-on Python experience for scientific computing, data analysis, visualization, simulation, or model implementation.
- Experience working with bioprocess or biological datasets, especially time-series data, assay results, spent media data, or process metadata.
- Familiarity with mechanistic, statistical, machine learning, or hybrid modeling approaches for biological or process systems.
- Strong analytical and problem-solving skills, with attention to data quality and scientific detail.
- Ability to work effectively in cross-functional teams and contribute to project activities under guidance from senior scientists or project leads.
Preferred
- Familiarity with PAT systems, bioreactor data infrastructure, LIMS/ELN/MES environments, cloud-based data workflows, or software-enabled scientific tools is a plus.
- Exposure to digital twin modeling, virtual experimentation, metabolic modeling, or process simulation is a plus.
Join Us
At Thermo Fisher Scientific, each one of our extraordinary minds has a unique story to tell. Join us and contribute to our singular mission--enabling our customers to make the world healthier, cleaner, and safer.
Compensation and Benefits
The salary range estimated for this position based in New York is $89,000.00–$149,800.00.This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:
A choice of national medical and dental plans, and a national vision plan, including health incentive programs
Employee assistance and family support programs, including commuter benefits and tuition reimbursement
At least 120 hours paid time off (PTO), 10 paid holidays annually, paid parental leave (3 weeks for bonding and 8 weeks for caregiver leave), accident and life insurance, and short- and long-term disability in accordance with company policy
Retirement and savings programs, such as our competitive 401(k) U.S. retirement savings plan
Employees’ Stock Purchase Plan (ESPP) offers eligible colleagues the opportunity to purchase company stock at a discount
For more information on our benefits, please visit: https://jobs.thermofisher.com/global/en/total-rewards
Source details
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- Pay
Compensation and Benefits The salary range estimated for this position based in New York is $89,000.00–$149,800.00. This position may also be eligible to receive a variable annual bonus based on company, team, and/or individual performance results in accordance with company policy. We offer a comprehensive Total Rewards package that our U.S. colleagues and their families can count on, which includes:
- Location & working pattern
Grand Island, New York, United States of America
- Experience working with bioprocess or biological datasets, especially time-series data, assay results, spent media data, or process metadata. - Familiarity with mechanistic, statistical, machine learning, or hybrid modeling approaches for biological or process systems. - Strong analytical and problem-solving skills, with attention to data quality and scientific detail.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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