Senior Manager, Statistical Innovation

Company Description

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 Description

The Senior Manager, Statistics provides statistical leadership to support the research and development organization for assigned projects. Specific areas of work may include clinical trials, patient safety, and global medical affairs. The Senior Manager works independently in partnership with experts in multiple disciplines to advance medicines to our patients.

Responsibilities

• Independently conduct research, experimentation, and methodology development for statistical, machine learning and AI models, including research and analyses to reinforce the current methodology/models, applying existing pipelines to validate results, generating results under different trial settings, and developing supporting materials such as slides and documentation.

• Support regulatory submission and product life-cycle management strategy planning and implementation. Provide statistical leadership for design, analysis and reporting for clinical or other scientific research programs. Independently develop protocols and statistical analysis plans (or product safety analysis plans/integrated summary of safety analysis plans/analysis plans for GMA evidence generation). Work independently to implement sound statistical methodology in scientific investigations.

• Represent the function on project team(s) to provide functional area input to asset development. Lead in identifying scientifically appropriate data collection instruments. Provide programming specifications for derived variables and analysis datasets. Guide Data Science and other functions in preparing for database lock. Ensure accuracy of data released for statistical analysis.

• Independently perform statistical analyses as per the analysis plan. Collaborate with Statistical Programming to ensure the delivery of high-quality outputs according to agreed-upon timelines. Identify and anticipate issues arising in the study design, conduct and propose scientifically sound approaches. Evaluate appropriateness of available software for planned analyses and assess needs for potential development of novel statistical methodology.

• Develop strategy for data presentation and inference. Ensure appropriate interpretation of statistical deliverables in collaboration with other functions. Collaborate in publication of scientific research. Ensure accuracy and internal consistency of reports and publications, including tables, listings, and figures.

• Work collaboratively with multifunction teams per agreed timelines. Clearly explain statistical concepts to non-statisticians. Provide responses to questions from clients and pursue analyses suggested by data under supervision.

• Support communications between assigned product team(s) and functional management. Build/drive cross-functional relationships and collaboration.

• (SSG) Lead statistical support for benefit-risk planning and assessment. Partner with crossfunctional team to develop output specifications to address both pre-planned safety analyses and ad hoc requests.

• (SSG) Lead within the Safety Statistics Group to implement strategic initiatives that address processes related to interpreting, monitoring, assessing, and reporting safety data to better characterize the safety profile of AbbVie products, improve efficiencies, and provide greater consistency across therapeutic areas.

• (GMA Stat) Support or lead GMA Statistics group in partnership with GMA, Clinical Research and Clinical Statistics to develop scientifically appropriate strategies for evidence generation, including GMA studies, presentations, and publications in assigned therapeutic area(s).

• (GMA Stat) Support or lead GMA Statistics to provide functional area input for life cycle management of products. Support or lead communications between assigned product team(s) and functional management. Build/drive cross-functional relationship and collaboration.

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.

• Have strong skills and experiences in conducting complex statistical analyses and modeling, including multiple testing, Bayesian analysis, mixed model analysis, survival endpoint analysis, etc.

• Have strong skills and experiences in conducting machine learning, deep learning and AI predictive modeling, including data-processing, model training, model tuning, and deployment

• Have strong skills and experiences in writing production-level code for end-to-end pipeline for complex statistical analyses and machine learning/AI modeling in both Python and R; familiar with tools like VS Code, Claude Code, GitHub, etc.

• Have strong real-world data processing and analysis skills with working experiences on ConcertAI, FlatIron, Optum databases

• High degree of technical competence and effective communication skills, both oral and written

• Able to identify data or analytical issues, and assist with providing solutions by either applying own skills and knowledge or seeking help from others

• Able to manage project timeline and quality of deliverables

• Able to build strong relationship with peers and cross-functional partners to achieve higher performance. Highly motivated to drive innovation by raising the bar and challenging the status quo

• Have strong leadership skills and experience in working/managing cross-cultural or oversea teams

• Pharmaceutical or related industry knowledge desired, including experience and understanding of drug development and life-cycle management in the regulated environment.

• (SSG) Some experience supporting safety-related projects (eg, ISS, benefit-risk assessment, signal detection) is preferred

• (GMA Stat) Competence in experimental and RWE study design, descriptive statistics, inferential statistics, statistical modeling, and statistical programming. Knowledge of methodologies for confounding control and bias minimization in observational studies preferred.

Additional Information

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

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