Associate Director, Forward Deployed Decision Science

AstraZeneca • Boston, MA

3d

About The Position

This is a business-facing, forward-deployed Decision Science role working alongside Alexion’s commercial leaders. The position owns the connection between business problems and the analytics used to address them, from understanding stakeholders’ needs to developing solutions and communicating practical recommendations that drive decisions and action.

The role applies data science, machine learning, analytical models, AI-enabled solutions, and decision frameworks to commercial questions, including sales effectiveness, targeting, patient finding, and promotional investment. It also involves designing and orchestrating AI agents and human-agent workflows, building scalable solutions on cloud platforms, and validating analytical and AI-generated outputs in accordance with data privacy requirements, de-identified data practices, and applicable AZ AI governance standards.

The successful candidate will operate independently, bring fresh ideas and expertise, and help teams use data, advanced analytics, and AI to improve commercial decision-making and focus resources where they can have the greatest impact for patients living with rare diseases.

Requirements

• Master’s degree or PhD in Data Science, Statistics, Biostatistics, Engineering, Economics, Applied Mathematics, or a related quantitative field.
• Typically 4 or more years of experience applying decision science, data science, advanced analytics, or quantitative methods to real business problems.
• Track record of applying analytics in a commercial environment, such as sales effectiveness, commercial operations, brand marketing, or an adjacent area such as supply chain.
• Hands-on experience with Databricks, AWS, Snowflake, Azure, or a comparable cloud/data platform.
• Practical, recent experience using AI-enabled approaches, coding agents, or agentic workflows, including human-agent interaction and orchestration.
• Working proficiency in Python and SQL, with practical experience in machine learning, predictive modeling, statistical analysis, and model validation.
• Strong communication and consulting skills, including the ability to engage non-technical leaders, simplify complex topics, and influence decisions without technical jargon.
• Ability to make an impact quickly, work autonomously, and bring expertise without requiring significant training to become effective.

Nice To Haves

• Experience in pharmaceutical, biotechnology, healthcare, life sciences, rare disease, or a healthcare practice within consulting or technology.
• Familiarity with commercial healthcare data such as claims, CRM, specialty pharmacy, patient services, or comparable datasets.
• Experience with marketing mix modeling, next-best action, segmentation, forecasting, patient identification, adherence, or field effectiveness.
• Experience with Power BI, Tableau, Qlik, or comparable tools for communicating analytical findings and enabling business decisions.

Responsibilities

• Partner with indication teams, Brand Marketing, Sales Operations, Insights, sales leadership, RDUs, and RAMs to understand their needs and priorities.
• Translate business questions into appropriate data science, machine learning, analytical, AI-enabled, or decision-framework solutions.
• Develop and apply analytical and machine learning approaches to commercial problems such as sales effectiveness, targeting, patient finding, and promotional investment.
• Own the connection between analytical work and business outcomes.
• Communicate sophisticated analytical output as clear, jargon-free recommendations stakeholders can act on.
• Design and orchestrate AI agents and human-agent workflows to accelerate analysis and decision-making.
• Use cloud platforms to build scalable and efficient analytical solutions.
• Operate independently, challenge the status quo, and bring ideas and expertise that strengthen the team’s capabilities.
• Use sound statistical judgment and validate AI-generated outputs while following data privacy requirements, de-identified data practices, and applicable AZ AI governance standards.

What This Job Offers

• Job Type: Full-time
• Career Level: Director