Role at a glance
- Job function
-
AI & Data Data Science
- Salary
- Not Disclosed
- Location
- Boston, Massachusetts, United States
- Employment
- Full-time
- Experience
- Relevant experience: Typically 4+ years of experience applying decision science, data science, advanced analytics, or quantitative methods to real business problems. Strong and recent experience with modern AI and analytics is more important than total years alone.
- Education
- Master's degree or PhD in Data Science, Statistics, Biostatistics, Engineering, Economics, Applied Mathematics, or a related...
Spotted an issue?
We’ll check it against the original posting.
Role Summary
This forward-deployed Decision Science role sits alongside commercial leaders to understand their challenges and shape them into analytical and AI-enabled solutions. The role focuses on delivering clear, practical recommendations that drive commercial decisions and action.
What You'll Do
- Partner directly with indication teams, Brand Marketing, Sales Operations, Insights, sales leadership, RDUs, and RAMs to understand...
- Convert business questions into data science, machine learning, analytical model, AI-enabled, or decision framework solutions
- Develop and apply analytical and machine learning approaches to commercial problems such as sales effectiveness, targeting, patient...
- Translate sophisticated analytical output into clear, jargon-free recommendations that stakeholders can act on
- Design and orchestrate AI agents and human-agent workflows that accelerate analysis and decision-making
- Use cloud platforms such as Databricks, AWS, Snowflake, or Azure as the foundation for scalable analytical solutions
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Essential qualifications include a quantitative master's or PhD, about 4+ years of applied decision science or analytics experience, commercial analytics track record, cloud platform experience, recent AI and agentic workflow experience, Python and SQL proficiency, and stakeholder communication skills. Desirable qualifications include life sciences or healthcare experience, commercial healthcare data familiarity, commercial analytics use cases, and visualization tool experience.
Required
- Master's degree or PhD in Data Science, Statistics, Biostatistics, Engineering, Economics, Applied Mathematics, or a related...
- Typically 4+ years of experience applying decision science, data science, advanced analytics, or quantitative methods to real business...
- Track record of applying analytics in a commercial environment such as sales effectiveness, commercial operations, brand marketing, or a...
- 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...
- Working proficiency in Python and SQL, with practical experience in machine learning, predictive modeling, statistical analysis, and...
- Strong communication and consulting skills, with ability to engage non-technical leaders and influence decisions without relying on...
- Ability to make an impact quickly and operate with autonomy
Preferred
- Experience in pharmaceutical, biotechnology, healthcare, life sciences, rare disease, or a healthcare practice within consulting or...
- Familiarity with commercial healthcare data such as claims, CRM, specialty pharmacy, patient services, or comparable datasets
- Experience with commercial analytics use cases such as marketing mix modeling, next-best action, segmentation, forecasting, patient...
- Experience with Power BI, Tableau, Qlik, or comparable visualization tools
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Associate Director, Forward Deployed Decision Science
About the Role
Do you want to be the person the business calls when a hard commercial question needs a real answer? In this forward-deployed role, you will sit side by side with Alexion’s commercial leaders to understand their challenges first-hand, shape them into analytical and AI-enabled solutions, and bring the answers back in clear, practical language that drives decisions and action.
This is a business-facing Decision Science role - You will own the connection between the business problem and the analytics that solve it.
What You'll Do
• Partner directly with the business: Embed with indication teams, Brand Marketing, Sales Operations, Insights, sales leadership, RDUs, and RAMs to understand their needs and priorities.
• Translate needs into solutions: Convert business questions into the right mix of data science, machine learning, analytical models, AI-enabled solutions, or decision frameworks.
• Deliver measurable outcomes: Develop and apply analytical and machine learning approaches to commercial problems such as sales effectiveness, targeting, patient finding, promotional investment, and other relevant business use cases, and own the connection to business outcomes.
• Make the complex simple: Turn sophisticated analytical output into clear, jargon-free recommendations that stakeholders can act on with confidence.
• Lead with agentic AI: Design and orchestrate AI agents and human-agent workflows that accelerate analysis and decision-making, applying current AI-native approaches alongside established analytical methods.
• Build on the cloud: Use cloud platforms such as Databricks, AWS, Snowflake, Azure, or comparable environments as the foundation for scalable and efficient analytical solutions.
• Bring fresh thinking: Operate independently, challenge the status quo, and bring new ideas and expertise that can strengthen the team’s capabilities.
• Safeguard trust: Apply sound statistical judgment and validate AI-generated outputs while working within data privacy requirements, de-identified data practices, and applicable AZ AI governance standards.
What You'll Bring
Essential
• Education: Master’s degree or PhD in Data Science, Statistics, Biostatistics, Engineering, Economics, Applied Mathematics, or a related quantitative field.
• Relevant experience: Typically 4+ years of experience applying decision science, data science, advanced analytics, or quantitative methods to real business problems. Strong and recent experience with modern AI and analytics is more important than total years alone.
• Demonstrated business impact: Track record of applying analytics in a commercial environment such as sales effectiveness, commercial operations, brand marketing, or a relevant adjacent area such as supply chain.
• Cloud computing: Hands-on experience with Databricks, AWS, Snowflake, Azure, or a comparable cloud/data platform. Exact platform experience can vary.
• AI-native and agentic workflows: Practical, recent experience using AI-enabled approaches, coding agents, or agentic workflows, including human-agent interaction and orchestration.
• Technical foundation: Working proficiency in Python and SQL, with practical experience in machine learning, predictive modeling, statistical analysis, and model validation. Depth may vary by model family and use case; mastery of every method or library is not required.
• Stakeholder management: Strong communication and consulting skills, with demonstrated ability to engage non-technical leaders, simplify complex topics, and influence decisions without relying on technical jargon.
• Independent delivery: Ability to make an impact quickly, operate with autonomy, and bring new expertise rather than requiring significant training to become effective in the role.
Desirable
• Healthcare or life sciences: Experience in pharmaceutical, biotechnology, healthcare, life sciences, rare disease, or a healthcare practice within consulting or technology.
• Commercial data: Familiarity with commercial healthcare data such as claims, CRM, specialty pharmacy, patient services, or comparable datasets.
• Commercial analytics use cases: Experience with areas such as marketing mix modeling, next-best action, segmentation, forecasting, patient identification, adherence, or field effectiveness.
• Visualization: Experience with Power BI, Tableau, Qlik, or comparable tools for communicating analytical findings and enabling business decisions.
Why This Role Matters
Your work will help teams use data, advanced analytics, and AI more effectively to identify opportunities, improve commercial decision-making, and focus resources where they can have the greatest impact for patients living with rare diseases.
In our dynamic environment, be supported by the brightest minds working together side by side. Agile and collaborative, we work cross-functionally, as well as externally, to thrive at pace. Be appreciated for your contributions. Our culture of recognition and reward means each of us feels supported and empowered to step up and take responsibility. With all the tools you need to excel at every level, coupled with ongoing constructive coaching, there’s no better place to bring out your best.
Are you ready to bring new ideas and fresh thinking to the table? Brilliant! We have one seat available and we hope it’s yours.
Date Posted
22-Oct-2026Closing Date
04-Nov-2026Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.
About the company
AstraZeneca
Large Enterprise
AstraZeneca is a global biopharmaceutical company dedicated to the research, development, and commercialization of innovative medicines. Headquartered in Cambridge, UK, the company focuses on areas such as oncology, cardiovascular, renal, metabolism, and respiratory diseases, striving to deliver life-changing treatments to patients. With a strong commitment to scientific excellence and collaboration, AstraZeneca invests in cutting-edge technologies and partnerships to drive advancements in healthcare. The company is also committed to sustainability and corporate responsibility, aiming to make a positive impact on communities worldwide.