About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job DescriptionTrial Surveillance & Analytics (TSA) is a newly formed center of excellence in Data & AI Acceleration, part of AbbVie's Data and Statistical Sciences organization. Our mission is to transform how AbbVie conducts ongoing clinical trial surveillance — integrating trial data, analytics and AI so that study teams and patient safety colleagues see emerging safety and efficacy signals early, and can act on them with confidence. This is work upstream, inside ongoing clinical trials, where insight can still change decisions for the study and for patients.
The Senior Manager, Trial Surveillance & Analytics is a hands-on, full-stack data scientist who takes a surveillance question from intake to a working solution. You will work in a small team that owns a capability end to end — from the data, through the analysis, to the tool that study teams use — and you will own your solutions from problem statement to a working product that people use. The team is AI-native from day one: agentic coding and AI agents are part of how we work, with room to experiment and to scale what works. You will combine depth in one area (such as statistical programming and reporting, data integration, data visualization, data science and machine learning, or data and software engineering) with enough breadth across clinical data, analytics and AI to deliver on your own, with the support of the team. As an early member of a new center of excellence, you will help define how it works, the standards it sets and the capabilities it builds, partnering across Global Patient Safety, therapeutic area clinical development teams, Statistics, Statistical Programming and data engineering across the portfolio.
Key Responsibilities:
- Frame surveillance problems with stakeholders before building: understand the decision to be supported, design for adoption, and iterate with users.
- Design and build data pipelines and analysis-ready, integrated data on SDTM, ADaM and integrated databases to support safety and efficacy surveillance.
- Lead blinded, standardized analytics across studies and compounds to detect emerging safety and efficacy signals early.
- Deliver reporting — tables, listings and figures, safety reports and listings — and automate it wherever possible.
- Develop applications, dashboards and self-service tools that study teams and patient safety colleagues use themselves; drive their adoption and measure their use.
- Apply generative and agentic AI across the analysis workflow, build AI agents on the clinical data foundation, and measure the gain in time and quality.
- Integrate clinical trial and real-world data where the science requires it, assessing comparability and data quality first.
- Lead projects and small cross-functional pods; coach and mentor team members. May include indirect supervision of employees and contract staff.
- Represent the team in cross-functional forums and communicate technical concepts and results clearly to non-technical audiences.
- Ensure adherence to applicable regulations, Good Clinical Practice (GCP), ICH guidelines, AbbVie Standard Operating Procedures (SOPs) and functional quality standards.
Minimum Qualifications:
- MS (with 8+ years of experience) or PhD (with 4+ years of experience) in Statistics, Biostatistics, Bioinformatics, Machine learning and AI or a highly related field.
- Experience may be in pharmaceutical, biotech, health technology or related industries.
- Strong hands-on programming in R and Python, plus SQL and version control (e.g. Git), with a track record of writing production-quality code for end-to-end analytical pipelines.
- Demonstrated experience applying generative or agentic AI to analytical or programming work, with measurable results.
- Experience working with clinical trial data (e.g. CDISC SDTM/ADaM) and/or real-world data (e.g. EHR, claims, registries).
- A track record of building analytical tools or solutions that were adopted and sustained by their users.
- Strong communication skills, including the ability to explain analytical and technical concepts in plain language and to influence cross-functional partners without direct authority.
Preferred Qualifications:
- Experience designing and building agentic AI systems (e.g. multi-step agents, tool use, retrieval and evaluation), with a track record of solutions delivered and used in production.
- Experience in clinical development, drug safety, pharmacovigilance, clinical trial monitoring or regulatory evidence generation.
- Knowledge of clinical trial design and of methods for real-world evidence, such as cohort definition, confounding control and external comparators.
- Experience building interactive visualizations and data apps with modern frameworks (e.g. Plotly / Dash, Streamlit, Shiny, React / D3) and deploying on cloud platforms (e.g. AWS).
- Familiarity with SAS.
- Experience leading cross-functional initiatives; formal business or leadership training is a plus.
- Publications, presentations or community leadership in data science, statistics or AI.
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
Skills Required
- MS in Statistics, Biostatistics, Bioinformatics, Machine Learning, AI, or a related field with 8 or more years of experience, or PhD in a related field with 4 or more years of experience
- Experience in pharmaceutical, biotech, health technology, or a related industry
- Strong hands-on programming experience in R and Python, plus SQL and version control such as Git
- Experience writing production-quality code for end-to-end analytical pipelines
- Demonstrated experience applying generative or agentic AI to analytical or programming work with measurable results
- Experience with clinical trial data such as CDISC SDTM or ADaM and/or real-world data such as EHR, claims, or registries
- Experience building analytical tools or solutions adopted and sustained by users
- Strong communication skills and ability to explain analytical and technical concepts to nontechnical audiences
- Experience designing and building agentic AI systems with multi-step agents, tool use, retrieval, and evaluation
- Experience in clinical development, drug safety, pharmacovigilance, clinical trial monitoring, or regulatory evidence generation
- Knowledge of clinical trial design and real-world evidence methods, including cohort definition, confounding control, and external comparators
- Experience building interactive visualizations and data applications with Plotly, Dash, Streamlit, Shiny, React, or D3
- Experience deploying applications on cloud platforms such as AWS
- Familiarity with SAS
- Experience leading cross-functional initiatives
- Publications, presentations, or community leadership in data science, statistics, or AI
AbbVie Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AbbVie and has not been reviewed or approved by AbbVie.
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Retirement Support — Retirement programs are portrayed as a standout, with a dollar‑for‑dollar 401(k) match up to 6% and an additional annual company contribution based on age and service. Feedback suggests this materially boosts perceived total compensation for many U.S. employees.
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Parental & Family Support — Paid parental and caregiver leave are emphasized, including up to 12 weeks of fully paid parental leave for all parents and 4 weeks of paid caregiver leave in the U.S. Feedback suggests these policies are a meaningful differentiator for employees balancing family needs.
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Leave & Time Off Breadth — Time off is described as extensive, with tiered vacation that scales with tenure, 17 company holidays, and two paid volunteer days in the U.S. Feedback suggests the breadth of leave contributes notably to overall benefits satisfaction.
AbbVie Insights
What We Do
AbbVie is a global biopharmaceutical company focused on creating medicines and solutions that put impact first — for patients, communities, and our world. We aim to address complex health issues and enhance people's lives through our core therapeutic areas: immunology, oncology, neuroscience, eye care, aesthetics and other areas of unmet need.
