Skills this job asks for
LeadershipMachine learningTranslationPythonAWSGoogle CloudTensorFlowPyTorch
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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 177 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 Abbvie US LLC paid sponsored hires in similar roles10 certified filings for “ASSOCIATE DIRECTOR, STATISTICS” (Data Scientists) in IL: $117k–$165k, median $151k.
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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 177 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 Abbvie US LLC paid sponsored hires in similar roles
- 10 certified filings for “ASSOCIATE DIRECTOR, STATISTICS” (Data Scientists) in IL: $117k–$165k, median $151k. Most were filed at wage level IV (50%) — 4 lottery entries, ≈61% 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
This role leads digital transformation for PDS&T Biologics laboratory operations. The successful candidate will design, develop, and execute a comprehensive data and digital strategy that delivers measurable value to scientists and accelerates biologics development.
As a member of the Center of Excellence (COE) leadership team for digital transformation and ML/AI within PDS&T Biologics, this leader will shape the AI and digital strategy and drive end-to-end digital integration across Biologics CMC. The COE includes representatives from each functional group. It serves scientists' needs and defines the data systems architecture that underpins knowledge management, advanced analytics, and predictive modeling.
Working closely with IT partners (IR and BTS), this leader will evaluate and optimize data systems, including ELN, sample management, laboratory automation, and scientific data platforms. The aim is seamless, automated capture and connectivity of biologics process and analytical data in line with FAIR data principles. The leader will also establish business and data governance with other PDS&T divisions, Development Sciences, Manufacturing, and Quality. They will prioritize use cases and workflow applications that advance digital maturity and measure impact through clear KPIs.
Responsibilities
• Provide leadership and subject-matter expertise for laboratory digital transformation, defining future-state capabilities and scalable digital solutions across PDS&T Biologics Development.
• Drive integration of laboratory instruments and systems to automate data capture and reduce manual data entry across scientific workflows.
• Serve as the digital product leader for ELN, sample management, laboratory automation, and scientific data platforms, translating scientific and business needs into scalable solutions.
• Advance FAIR data principles and data standardization to improve the findability, accessibility, interoperability, and reuse of scientific data for analytics, modeling, and digital applications.
• Own the continuous evolution of laboratory digital products, including system configuration, user experience, platform scalability, performance, and adoption.
• Partner with scientists, laboratory operations, Quality, Technical Operations, Data Science, IR, and BTS to streamline workflows, improve data quality, and accelerate R&D outcomes.
• Define KPIs and dashboards and communicate progress on initiatives to stakeholders.
• Influence leadership and cross-functional stakeholders to secure investments that align digital transformation with PDS&T Biologics business priorities.
• Represent scientists' needs and champion the work processes and culture that digital transformation requires.
• Support the COE book of work for digital transformation within PDS&T Biologics.
• Benchmark internally and externally to keep the data and digital strategy for biologics process and analytical development industry leading.
• M.S. or Ph.D. in life sciences or a science-based informatics discipline, with 10+ years of pharmaceutical/biotechnology industry experience, including at least 8 years in a relevant R&D or Operations function.
• Proven track record of enabling new digital or data management capabilities, beyond incremental improvements or routine system implementations.
• Technical proficiency in programming languages (e.g., Python, R) and cloud platforms (e.g., AWS, GCP).
• Familiarity with AI/ML platforms and tools (e.g., TensorFlow, PyTorch) relevant to biologics CMC workflows.
• Demonstrated ability to apply AI/ML techniques in biologics CMC development to optimize processes, strengthen data analysis, and enhance predictive modeling.
Applicable only to applicants applying to a position in any location with pay disclosure requ
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