Associate Director, Measurement and Evaluation-Wilmington, DE

At AstraZeneca, we're not afraid to do things differently. We're resetting expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, ground-breaking and cutting-edge methods and bringing unexpected teams together.

AstraZeneca is organized around two core business units, Biopharmaceuticals (BBU) and Oncology. The BBU focuses on development and commercialization of AstraZeneca’s Respiratory, Cardiovascular, Metabolic, Renal, and Infectious Disease therapeutic areas.

Strategic Field Operations (SFO) is a critical function, within Innovation and Business Excellence (IBEX), that enables success in the growth of the BBU business. Our ambition is to build an industry-leading organization which A) supports senior leadership with critical business decision making and B) empowers our Commercial teams through the generation of compelling insights and delivery of tools and capabilities to deliver impactful launches that change the practice of medicine for the benefit of patients.

Job description

The Associate Director of Measurement and Evaluation at AstraZeneca will be responsible for leading a range of analytical projects leveraging cutting-edge analytics that provide commercial teams measurable insights into commercial strategies and tactics. The role will work closely with Strategic Field Operations, brand teams, sales, forecasting, 3rd party vendors and other cross-functional business partners to understand opportunities and transform insights into business actions.

The identified candidate should have strong analytics capabilities combined with strong communication and influencing skills. As such, those who will qualify for this position are both technically sound and have the ability to be a proactive internal consultant, adding value to AstraZeneca's commercial organization beyond their analytical prowess through their understanding of secondary data, industry knowledge, and track record of innovative and impactful decision support.

Key responsibilities

• Generate insights relating to field force deployments (including omnichannel) that create a competitive advantage for our commercial organization.  Examples include conducting test / control analysis, leverage promo response capabilities and other multivariate and univariate approaches. 
• Conduct hands on analytics as well as collaborate / manage internal analytics partners and 3rd party vendors to prioritize workload and identify the right analytics approach for the business question at hand.
• Collaborate with matrix teams (sales, marketing, advanced analytics SMEs, IT, external vendors, etc.) to ensure effective and efficient deployment of capabilities.
• Serve as a subject matter expert to internal stakeholders on the use of advanced analytics and field related insight generation.
• Develop a deep understanding of the BBU core markets, their data and their analytical needs.

Essential requirements

• Quantitative Master’s or PhD degree from an accredited college or university is required in one of the following or related fields: Engineering, Operations Research, Management Science, Economics, Statistics, Math, Physics, Computer Science or Data Science.

• 5+ years of hands-on experience in applying advanced analytics methods to large and disparate datasets preferably in the context of Omnichannel marketing, specifically:
  • Statistical Analysis and Modelling: (e.g. Design of Experiments, Time Series Analysis, Regression Analysis, Bayesian methods, etc),
  • Machine Learning and Artificial Intelligence.
  • Optimization and Simulation.
• Hands-on experience and deep theoretical expertise in Design of Experiments
• Hands-on experience and deep theoretical expertise in Deep learning models (CNN, RNN)
• Expert-level programming experience with either Python or R.
• Knowledge of SQL and/or other data management languages (e.g. Hive, Impala, Hbase, etc)

Desirable Requirements

• Pharma industry knowledge.
• Strong leadership and interpersonal skills with demonstrated ability to work collaboratively with a significant number of business leaders and cross-functional business partners.
• Strong organizational skills and time management; ability to handle diverse range of simultaneous projects.
• Experience with machine learning libraries and tools, such as Scikit-learn, Tensorflow, Keras and PyTorch.