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Machine learningPythonSQLPyTorchLeadershipEnglish
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 47 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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✓
What Sanofi US Services INC paid sponsored hires in similar roles4 certified filings for “Scientist, Disease Data Analytics” (Molecular and Cellular Biologists) in MA: $92k–$135k, median $103k.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 47 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Sanofi US Services INC paid sponsored hires in similar roles
- 4 certified filings for “Scientist, Disease Data Analytics” (Molecular and Cellular Biologists) in MA: $92k–$135k, median $103k. Most were filed at wage level II (50%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
Job Title: Protein ML Senior Principal Data Scientist
Location: Waltham, MA
About the Job:
As Protein ML Senior Principal Data Scientist within our Vaccines R&D Data and Computational Sciences team, you'll design and deploy state-of-the-art machine learning models that predict protein properties and accelerate the development of next-generation vaccines. Ready to get started?
In this role, you will harness the power of protein language models and foundational AI to predict immunogenicity, stability, and manufacturability — properties that are critical to bringing safe, effective vaccines to the world. Working at the interface of computational and experimental science, you will collaborate closely with antigen design and bench lab teams to iteratively refine protein property predictors and translate computational insights into real-world vaccine candidates.
Join the team protecting half a billion lives every year with next-gen science, mRNA innovation, and AI-driven breakthroughs. In Vaccines, you'll help advance prevention on a global scale - and shape the future of immunization.
About Sanofi:
We're an R&D-driven, AI-powered biopharma company committed to improving people's lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people's lives.
Main Responsibilities:
• Develop state-of-the-art protein property prediction models with a focus on immunogenicity, stability, and manufacturability to support vaccine design.
• Leverage and refine language-based foundational protein representations to accelerate the identification and optimization of vaccine candidates.
• Analyze complex relationships between protein sequences, structures, and functional data to uncover generalizable representations applicable across vaccine programs.
• Collaborate with structural biology, protein design, and bench lab teams to shape the strategy for protein modeling and to iteratively improve model quality
• Maintain the modeling codebase according to best coding practices, ensuring results are robust, reproducible, and well-documented.
• Mentor and upskill colleagues on the latest advances in protein modeling tools and techniques, fostering a culture of continuous learning and scientific rigor.
• Communicate scientific findings clearly and compellingly to a broad range of internal and external stakeholders, adapting the level of detail to each audience.
About You :
Education
• PhD degree in Computational Biology, Data Science, Applied Mathematics, Biophysics or a closely related field
Experience
• 2 + years of industry or academic setting experience.
Preferred Qualifications
• Exceptional track record in computational biology, encompassing protein language models, biophysics, and the development of AI-based predictive models; prior experience with immunogenicity predictors is a plus.
• Advanced proficiency in Python, R, and SQL, with hands-on experience in PyTorch and AI-based structural modeling tools such as AlphaFold, OpenFold, and Boltz
• Deep knowledge of protein representation models such as ESM
• Familiarity with molecular dynamics, next-generation sequencing analysis, and deep mutational scanning is an advantage.
• Familiarity with agentic tools such as Claude Code for automated software engineering strongly preferred.
• Demonstrated ability to communicate fluently — in writing and in person — across computational and bench lab teams, adapting messaging to diverse audiences including senior leadership
• Proven ability to mentor junior colleagues and lead collaboratively in the area of protein modeling.
• St
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