Data Scientist - Supply Chain Domain - Pharma

Accountabilities:

As a Supply Chain Data Scientist, you will develop specialized knowledge of AstraZeneca's supply chain, collaborating closely with stakeholders to understand and address key business issues using Data Science solutions. Additionally, you will foster the development of Data Science capabilities within the supply chain, including advancements in Artificial Intelligence (AI) and Machine Learning (ML). Your role will be crucial in promoting the value that Data Science brings to 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.)

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

- Two years of experience with knowledge graphs in a popular graph database framework, including applying graphs in AI/ML projects

- Proficiency in advanced statistical modeling, machine learning, data mining, and unstructured data analytics in corporate and/or academic research settings

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

- Two years of experience developing machine learning methods, including expertise in techniques such as clustering, regression, optimization, recommendation systems, neural networks, and more

- Proficiency in programming for data analysis, ideally using Python, SQL, or R

Desirable Skills/Experience:

- Experience in the pharmaceutical industry

- Demonstrated expertise in artificial intelligence, machine learning, data science, and other relevant technical domains