Senior Manager - Decision Science

Are you ready to turn Decision Science and AI into measurable outcomes that speed life-changing medicines to patients? Do you want to lead high-impact work where meticulous evaluation, rapid iteration, and clear evidence of improvement guide every release?

As Senior Manager – Decision Science, you will lead the complete process to build, evaluate, and deploy decision solutions powered by artificial intelligence. These solutions support our data insights and intelligent technology goals throughout the enterprise. You will champion an evaluation-first approach—selecting the right methods, defining outcome-aligned metrics, and validating gains in efficiency, quality, risk, and decision outcomes—so that models and AI products aren’t just built, they’re proven to work in the real world.

You will orchestrate multidisciplinary teams to move from problem framing to production at pace, using versioned 45-day delivery cycles that deliver incremental, measurable value. Working closely with business, technology, and governance partners, you will ensure solutions are robust, transparent, and compliant. We thrive on in-person collaboration and typically spend at least three days each week together in the office to connect, move fast, and challenge assumptions.

• Lead AI and decision intelligence solution development from problem framing through production and adoption. Select suitable methods including statistical, ML, optimization, simulation, and GenAI. Define metrics aligned with business and process outcomes. Use synthetic and historical data along with real-world validation. Show measurable improvements in decisions, processes, or outcomes. Manage delivery in 45-day versioned cycles with incremental value each release.
• Team Leadership and Technical Execution: Coordinate decision scientists, software engineers, and infrastructure groups to translate analytical ideas into secure, maintainable, production-grade solutions; set direction on feature building and data strategy, model evaluation, validation and monitoring, and trade-offs between accuracy, explainability, speed, and cost; foster strong decision science practices including peer review, reproducibility, and responsible AI.
• Delivery, Governance and Reporting: Track project progress, benefits realization, and budget with data-driven status updates; ensure solutions meet regulatory, compliance, and governance standards in regulated and risk-sensitive domains; identify and mitigate delivery, technical, data, and adoption risks throughout the lifecycle.
• Partner with business, IT, data platform, and risk/compliance teams to align priorities and dependencies. Resolve constraints and accelerate time-to-value without compromising quality. Act as a translator between decision science depth and business outcomes, especially for senior collaborators.
• Contribute to the intelligent systems and analytics platform roadmap by prioritizing capabilities. These capabilities enable repeatable evaluation and experimentation, scalable implementation and oversight of models, and reduce cycle time from idea to impact. Influence standards for MLOps, model evaluation, performance tracking, and cost optimization.
• ML and Analytics Enablement: Ensure tools, infrastructure, and workflows support rapid experimentation and evaluation, reliable deployment and monitoring of ML models, and continuous improvement across versions; improve reliability, scalability, and time-to-value of analytics and AI solutions.

• Confirmed experience leading initiatives in artificial intelligence and decision analytics from concept to production, with demonstrable business impact.
• Strong grounding in model selection, evaluation methods, validation techniques, and performance measurement.
• Experience delivering solutions using agile delivery methods, including short, versioned delivery cycles.
• Ability to coordinate the work of decision scientists, engineers, and platform teams.
• Strong project and delivery leadership skills, including progress, risk, and budget tracking.
• Excellent collaborator leadership skills, with the ability to connect analytical insight to business outcomes.

• Experience delivering AI/ML platforms and analytics products in cloud environments (Azure, AWS, or GCP) with MLOps practices.
• Background in pharma, biotech, or other regulated industries, with an understanding of data, model risk, and governance.
• Expertise in agile delivery at scale, product-style value tracking, and benefits realization.
• Ability to balance model performance, explainability, compliance, and cost.
• Familiarity with cost management and performance optimization for data and ML workloads.
• Experience working with synthetic data generation, offline experimentation, and controlled real-world validation.

Join a distributed team that blends science, decision intelligence, and engineering craft to turn ambitious ideas into tangible impact for patients. We bring unexpected teams into the same room to unlock inventive thinking, pair ground breaking technology with rigorous governance, and move at pace while doing things the right way. We are coordinated throughout the organization to tackle varied, sophisticated problems. We streamline processes, improve data flow, and elevate decision quality at scale. Your work will have a clear line of sight to outcomes that matter. We value kindness alongside ambition, give you the autonomy to own your ideas, and surround you with curious peers who will challenge and support you as you grow.

Own the roadmap for evidence-based AI decisions and see your impact ripple across the enterprise and to patients—take the next step and introduce yourself today!

Date Posted

Closing Date

AstraZeneca embraces diversity and equality of opportunity.  We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills.  We believe that the more inclusive we are, the better our work will be.  We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics.  We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.