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 atwww.abbvie.com. Follow @abbvie onLinkedIn,Facebook,Instagram,XandYouTube.

While the AI innovation race in Biopharma is focused on Drug discovery, Product Development/ CMCrepresentsthe next barrier/ bottleneck. The complexity of biological systems, the rigor of regulatory expectations, the pace of pipeline growth, and the enormous value at stake make this one of the highest-leverage domains for applied data science and AI in the entire pharmaceutical value chain.

We here at BTS - PDST, are building a dedicated, AI-native team that is drivingcutting edgeprograms across early stage, late stage and commercial product development to accelerate E2E product development and launch, maximize yields of block buster products. Through our deep collaboration with PDST scientists we are boldly reimagining howAbbViecan bring our pipeline products and lifesaving drugs to patients faster, safer and in cost effective manner fueled by AI.

Late-Stage BiologicsData Scientistis a senior individual contributor role built for a scientist-engineer who thinks in systems, builds with purpose, and leads through technical credibility. Thisroleis a shaper of outcomes. You will embed AI and advanced analytics directly into AbbVie's late-stagebiologicspipeline including process characterization studies, technology transfer to commercial manufacturing sites, processrobustnessandcommercial lifecycle optimization. You will architect data solutions, build and deploy predictive models, andestablishthe analytical foundation thatenables AbbVie to make faster, smarter, more defensible decisions at every stage of commercialbiologicsdevelopment.

• Enterprise-scale scope: Enterprise-scale biologics portfolio spanning clinical, commercial, and lifecycle stages
• Building AI playbook for the future: First-in-AbbVie and first-in-biologics analytical approaches; you build the AI playbook for the future
• Growth and Impact: Direct impact on regulatory submissions, commercial readiness, and manufacturing decisions through deep cross-functional exposure to manufacturing, quality, regulatory, and scientific leadership
• Mission: Every model you build helps ensure safe, reliable medicines reach patients at scale

Responsibilities

Process Intelligence & Predictive Analytics

• Design, build, and deploy predictive and prescriptive models that support process robustness assessment, control strategy optimization, and commercial process validation across late-stage biologics programs.
• Develop multivariate and time-series modeling approaches toidentifycritical process parameter interactions, predict process drift, and support proactive deviation prevention at commercial manufacturing sites.
• Apply advanced statistical and machine learning methods including dimensionality reduction, anomaly detection, Bayesian inference, and hybrid mechanistic-empirical models to characterize complex bioprocess behavior andestablishmeaningful process design spaces.
• Build andmaintaingolden batch frameworks and optimization models that serve as living benchmarks for process performance across sites and over time.

Technology Transfer & Cross-Site Analytics

• Lead the development of data infrastructure and analytical tools that enable intelligent, data-driven technologytransferfrom development to commercial manufacturing reducing transfer risk and compressing timelines.
• Build cross-site process intelligence systems that allow PDST and manufacturing teams to compare, contextualize, and act on process data across geographically distributed sites and diverse equipment trains.
• Partner with manufacturing science and quality teams to define data requirements,establishdata standards, and ensure analytical continuity from process development through commercial operations.

Solution Architecture & AI Strategy

• Serve as a solution architect for AI and analytics initiatives within PDST evaluating problems holistically and selecting the right combination of approaches, whether that means classical statistical models, modern machine learning, retrieval-augmented knowledge systems, orchestrated analytical agents, or purpose-built hybrid mechanisms.
• Establish modeling frameworks, validation protocols, and deployment standards that are scientifically rigorous, regulatory-aware, and built for long-term maintainability in aGxPenvironment.
• Contribute to PDST's AI roadmap byidentifyinghigh-value opportunities, scoping solutions, and advocating for the infrastructure investments needed to sustain analytical excellence.

Data Strategy & Governance

• Define and drive data strategy for late-stage biologics programs including data acquisition planning, ontology development, quality standards, and integration across LIMS, MES,historian, and electronic batch record systems.
• Champion data literacy and modeling best practices across PDST and its manufacturing and quality stakeholder community.
• Ensure that models, analyses, and data assets are documented, version-controlled, andmaintainedto standards consistent with regulatory expectations including 21 CFR Part 11, ICH Q8/Q9/Q10, and relevant FDA/EMA guidance.

Stakeholder Engagement & Scientific Leadership

• Translate complex analytical outputs into clear, actionable scientific narratives for manufacturing, quality, regulatory, and executive audiences.
• Influence technical decision-making without formal authority earning trust through scientific rigor, transparentmethodology, and demonstrated business impact.
• Mentor junior scientists and analysts withinPDST;contribute to a culture of technical excellence, intellectual curiosity, and continuous improvement.

Required:

• Bachelor's Degree in Computer Science or a related discipline with 7 years experience in IT and application program development; or Master's Degree with 6 years experience; or PhD with 2 years experience.
• Respective years of hands-on experience building and deploying data science or machine learning solutions in a scientific or engineering-intensive environment.
• Expert-level Pythonproficiency; deep familiarity with the scientific Python ecosystem (NumPy, pandas, scikit-learn,PyTorchor TensorFlow,modern data engineering (cloud, big data, pipeline orchestration)
• Strong foundationinbusiness analytics, with mastery of tools such as R, Dataiku, AWS SageMaker, Spark, Tableau
• Strong foundationindata science methods,statistical modeling, experimental design, multivariate analysis, and uncertainty quantification with the ability to choose, justify, and communicate methodological choices rigorously
• Familiarity withknowledge graph, retrieval-augmented, or orchestrated AI/LLM-based systems applied to scientific or technical domains
• Experience applying data science in aGxP-regulated environment, with working knowledge of FDA/EMA expectations for process validation, continued process verification (CPV), and control strategy.
• Familiarity withMLOpsprinciples, model lifecycle management, or deployment of analytical tools in regulated or enterprise environments.
• Ownership orientation: you define your own problem space, drive solutions to completion, and hold yourself accountable to outcomes not just outputs.
• Solution-architect instinct: you think before you build, consider the full landscape of available approaches, and choose tools based on fit-for-purpose reasoning rather than familiarity or trend.
• Scientific integrity: you build models you can explain, defend, and improve and you apply the same standard to the work of others.
• Influence through credibility: you earn the confidence of scientists, engineers, and quality professionals by being right, being clear, and being useful not by title or volume.
• Bias for impact: you are drawn to problems where the stakes arehighand the analytical opportunity is real, and you are energized rather than intimidated by ambiguity.

Preferred:

• Advanced degree (M.S. or Ph.D.) in Data Science, Biostatistics, Chemical or Biochemical Engineering, Computational Biology, or a closely related quantitative discipline.
• 5+ years of hands-on experience building and deploying data science or machine learning solutions in a scientific or engineering-intensive environment.
• Direct experience inbiologicsmanufacturing, late-stage process development, or commercial bioprocess operations including familiarity with upstream (cell culture, fermentation) and/or downstream (purification, formulation) unit operations.
• Exposure tostability program analytics, comparability assessments, or post-approval change management from a data and modeling perspective.
• Experienceinworking withdata from diverselab andmanufacturing systems (LIMS, MES,DeltaV/historian,eBRplatforms) and building scalable data pipelines forprocessanalytics.
• Track recordof scientific communication publications, regulatory submissions, technical reports, or equivalent thatdemonstratesthe ability to convey complex analytical work clearly and credibly.
• Familiarity with technology transfer workflows, process characterization study design, or commercial process validation (PPQ/PV) in abiologicsor pharmaceutical context.

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state orlocal law:

• The compensation range described below is the range of possible base pay compensation that the Companybelieves ingood faith it will pay for this role at the timeof this posting based on the job grade for this position.Individualcompensation paid within this range will depend on many factors including geographic location, andwemayultimatelypaymore or less than the posted range. This range may bemodifiedin thefuture.
• We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick),medical/dental/visioninsurance and 401(k) to eligibleemployees.
• This job is eligible toparticipatein our long-term incentiveprograms.

Note: No amount of payis considered to bewages or compensation until such amount is earned, vested, anddeterminable.The amount and availability of any bonus,commission, incentive, benefits, or any other form ofcompensation and benefitsthat are allocable to a particular employeeremainsin the Company's sole andabsolutediscretion unless and until paid andmay bemodifiedat the Companys sole and absolute discretion, consistent withapplicable 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, visithttps://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

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https://www.abbvie.com/join-us/reasonable-accommodations.html