Jobs / United States / Astrazeneca Pharmaceuticals Lp
Associate Director, Oncology Clinical Intelligence & Applied Analytics
Astrazeneca Pharmaceuticals Lp · 🇺🇸 US - Waltham - MA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 99 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. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- 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. 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 Astrazeneca Pharmaceuticals Lp paid sponsored hires in similar roles1 certified filing for “Associate Director, Oncology Portfolio Analytics” (Management Analysts) in MD: $157k–$157k, median $157k. Most were filed at wage level II (100%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
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.
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Sponsor Radar — Astrazeneca Pharmaceuticals Lp
The US Department of Labor certified 99 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. USCIS also records 31 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Astrazeneca Pharmaceuticals Lp →
About the role
Are you ready to turn complex clinical and real-world data into evidence that shapes pivotal decisions in Oncology? Do you want your analytics to directly influence Phase 3 investments, trial design, and patient access? In this role, you will operate where evidence generation meets hands-on analytics, partnering with stakeholders to pinpoint the highest-value evidence gaps and leading the delivery that closes them. You will move seamlessly from portfolio-level prioritization with Global Product Teams to building rigorous multimodal patient models or external control arm analyses that inform development and access. Hematology is growing rapidly. As the technical specialist for clinical intelligence and real-world evidence, you will translate complex data into decision-ready insights, build persistent intelligence that compounds across use cases, and help steer how the portfolio advances for patients. Accountabilities: • Evidence Gap Prioritization : Partner with Hematology stakeholders and Global Product Teams to identify and prioritize evidence needs across the product lifecycle, including Phase 3 investment decisions, subpopulation discovery, and trial design. • AI and Causal Inference Analytics : Apply machine learning and causal inference to deliver robust answers on patient stratification, external control arm construction, prognostic risk adjustment, and treatment effect heterogeneity, ensuring analyses meet regulatory and HTA expectations. • Multimodal Patient Models : Deliver and validate patient-level models that integrate clinical, genomic, imaging, and real-world data for deployment in clinical trials or routine care, with emphasis on reproducibility and rigorous validation. • Decision-Ready Insights : Turn internal and competitor trial data, alongside real-world data, into clear insight on standard of care, patient pathways, benchmarking, and unmet need to sharpen development and access strategies. • Platform Enablement : Work with platform and tooling teams to bring new tools, agents, and experimental approaches into evidence generation, and build Hematology-specific intelligence that persists within the Phase 3 Investment Decision Intelligence Foundation. • Cross-Functional Collaboration : Connect strategic evidence needs with technical delivery, aligning outputs to development, regulatory, and access milestones; collaborate with Translational Science and Clinical Development to incorporate novel signals such as digital endpoints, pathology AI, and biomarker panels. Essential Skills/Experience: • Advanced degree (PhD or equivalent) in a quantitative discipline - epidemiology, biostatistics, computational biology, machine learning, health data science, or a related field. • 5+ years of experience spanning both evidence strategy and real-world evidence and/or advanced analytics and data science. • Strong methodological foundation in causal inference and observational study design, including propensity score methods, instrumental variables, target trial emulation, and comparative effectiveness research. • Hands-on experience with machine learning and multimodal modeling, including supervised and unsupervised methods, deep learning for imaging or molecular data, and integration of heterogeneous data types into patient-level models. • Experience building or contributing to external control arms, trial simulators, or prognostic models using real-world and/or clinical trial data. • Understanding of regulatory and health technology assessment (HTA) evidence standards, with the ability to design analyses that meet the evidentiary bar for submissions and payer engagement. • Proficiency in Python, R, and SQL, and familiarity with cloud-based analytics environments. Desirable Skills/Experience: • Domain