# Senior Manager, Forward deployed Decision Scientist at AstraZeneca

AstraZeneca is hiring a Senior Manager, Forward deployed Decision Scientist. Level rates it Builds AI ●●●●; you can [apply on Level](https://jobsbylevel.com/go/cd3086dc-23d7-48e2-8e42-d3b986ac5f40?utm_medium=ai-agent).

AI Level 4, AI centrality 82 out of 100. Canada - Mississauga.

## Details

- Company: [AstraZeneca](https://jobsbylevel.com/companies/astrazeneca)
- AI level: AI Level 4 (score 82 out of 100)
- Location: Canada - Mississauga
- Posted: October 16, 2026
- Apply: https://jobsbylevel.com/go/cd3086dc-23d7-48e2-8e42-d3b986ac5f40?utm_medium=ai-agent

## Prepare for this job

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## Description

When we bring different perspectives together, we unlock bold thinking that can help transform patients’ lives. In-person collaboration gives us the opportunity to connect, move quickly and challenge conventional thinking. That’s why we work, on average, a minimum of three days per week from the office, while balancing this with individual flexibility. The Senior Manager, Forward Deployed Decision Scientist is a hands-on role within the Decision Science group supporting Alexion’s Rare Disease Unit. Based in Mississauga, Ontario , you will partner closely with commercial teams to turn complex business questions into analytical solutions that support HCP engagement, patient opportunity assessment and commercial effectiveness. You will lead analytics projects from problem definition through model development, validation and implementation, collaborating with analytics leaders on priorities and methodology. You’ll bring together statistical expertise, machine learning and AI-assisted development using tools such as Snowflake Cortex AI and approved coding assistants. Patient-level analysis will use de-identified data within approved privacy, compliance and AI governance standards. What you’ll do Statistical & Predictive Analytics Apply statistical methods, experimental design and regression techniques to solve commercial business problems and clearly communicate findings, uncertainty and limitations. Develop, validate and deploy predictive and machine learning models, using appropriate approaches for small samples and class imbalance common in rare disease. Apply survival analysis, forecasting and causal inference methods to areas such as adherence, patient journeys, demand planning and commercial effectiveness. Commercial Data Science Develop advanced analytics solutions across marketing mix optimization, next-best-action, patient identification, adherence and retention, segmentation and competitive intelligence. Use healthcare data sources, including claims, specialty pharmacy, CRM and other real-world datasets, to generate actionable insights. Translate model outputs into clear recommendations that enable better commercial decision-making. AI-Enabled Analytics Use Snowflake Cortex AI and approved AI-assisted development tools to accelerate analytical development, feature engineering and prototyping. Critically evaluate AI-generated code and analytical outputs for statistical accuracy, reliability and appropriate application. Help develop evaluation approaches and guardrails that support responsible and effective use of AI in analytics. Data Privacy, Governance & Model Quality Work with de-identified patient-level data in accordance with applicable privacy, regulatory and organizational requirements. Apply model explainability, bias and fairness assessments, validation, monitoring and appropriate governance controls. Maintain clear documentation and auditability across analytical methods, models and recommendations. Collaboration & Leadership Lead assigned analytics projects, manage milestones and proactively identify risks and dependencies. Partner across Brand, Market Access, Patient Services, Field and other teams to understand business needs and translate analytics into action. Communicate complex analytical concepts clearly to both technical and non-technical audiences. Contribute to peer reviews, knowledge sharing and coaching across the team. Essential Qualifications Bachelor’s degree in Statistics, Biostatistics, Data Science, Econometrics, Applied Mathematics, Computer Science or a related quantitative field, or equivalent relevant experience. Strong experience in data science, applied statistics or quantitative analytics, with hands-on delivery of predictive models or advanced analytics solutions. Strong foundation in statistical modeling, machine learning, model validation and experimental design. Proficiency in Python and SQL , with experience using relevant statistical and machine learning libraries. Experience

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