AstraZeneca - Data Scientist - Supply Chain Domain (10-15 yrs)

Role : Supply Chain Data Scientist

Why AstraZeneca?

At AstraZeneca when we see an opportunity for change, we seize it and make it happen, because any opportunity no matter how small, can be the start of something big. Delivering life-changing medicines is about being entrepreneurial - finding those moments and recognising their potential. Join us on our journey of building a new kind of organisation to reset expectations of what a bio-pharmaceutical company can be. This means we're opening new ways to work, pioneering cutting edge methods and bringing unexpected teams together.

Introduction to role :

Supply Chain Digital & Analytics is charged with ensuring our stakeholders have access to the data, insights, and innovations required to deliver against our Supply Chain Digital Strategy. Tasked with supporting a rapidly expanding set of projects and analytical demand, we are seeking Data Scientists, who can help advance the field within the Supply Chain Organization and deliver meaningful solutions that strive to solve our biggest challenges.

Accountabilities :

As a Supply Chain Data Scientist, you will build domain-specific knowledge regarding supply chain in AstraZeneca, working closely with stakeholders to understand key business problems and bring Data Science solutions to resolve. You will also advance the development of internal capability for Data Science within supply chain, including Artificial Intelligence (AI), and Machine Learning (ML). Your role will be pivotal in driving awareness of the value Data Science offers our global supply chain.

Essential Skills/Experience :

- Bachelor's degree in a quantitative field (e.g., applied mathematics, computer science, physics, economics, engineering, statistics, operations research, quantitative social science, etc.)

- Minimum of two years experience in Supply Chain Projects (demand planning & forecasting inventory, optimization, logistics, network design, segmentation, and S&OP) in sophisticated and complex environments

- Two years experience working with knowledge graphs in a popular graph database framework, including using graphs in AI/ML projects.

- Advanced statistical modeling, machine learning, data mining, unstructured data analytics in corporate and/or academic research environments

- Strong quantitative and analytical skills with a minimum of two years of experience with data science tools, including Dataiku, SAS, AWS Sagemaker

- Two years of developing machine learning methods, including familiarity with techniques in clustering, regression, optimization, recommendation, neural networks, and others

- Familiarity with programming for data analysis; ideally Python, SQL, or R

Desirable Skills/Experience :

- Pharmaceutical industry experience

- Proven knowledge in artificial intelligence, machine learning, data science, and other relevant technical domains