Data Science Intern 2025 Working in Science Internship Program

Key Skills

AWS, Data Analytics, Data science techniques, Effective communication skills, Github, Jupyter Notebook, Machine learning techniques, Natural Language Processing (NLP), Presentation skills, Python Programming, SQL

Job Description

The Quality Investigation & Analytics team is part of the Process, Quality & Transformation within Biopharma Clinical Operations (BioPharma ClinOps). We provide data-driven insights to enhance inspection readiness and regulatory compliance, thereby empowering study teams to deliver clinical studies. The team is also responsible for delivering Quality Management reporting and solutions within R&D. Additionally, we manage project oversight of the Quality Management Systems analytics and Study Quality Oversight roadmap to ensure timely and efficient delivery of solutions to the business.

We are seeking a motivated and talented Data Science Intern to join our dynamic team. The internship will offer practical experience in data analysis, machine learning, and the visualization of complex datasets. This is an excellent opportunity for individuals looking to gain hands-on experience in the pharmaceutical industry while contributing to meaningful projects.

Key Responsibilities:

• Collaborate with data scientists and other team members to develop and implement data-driven solutions.

• Assist in the collection, cleaning, and preprocessing of data from various sources.

• Perform exploratory data analysis to uncover insights and trends.

• Support the development of predictive models and machine learning algorithms.

• Visualize data and model outputs to effectively communicate findings.

• Contribute to the preparation of technical reports and presentations

Requirements:

• Currently pursuing a BSc, MSc, or PhD in Data Science, Computer Science, Statistics, Mathematics, Physics, or a related field.

• Experience in machine learning, including the ability to develop and deploy predictive models.

• Experience working with or building ETL (Extract, Transform, Load) pipelines in addition to standard data tools (e.g., SQL, AWS).

• Experience working through data science use cases.

• Proficiency in Python, in addition to other data science tools (e.g., Jupyter Notebooks, GitHub).

• Ability to work autonomously with a capacity to drive projects forward.

• Ability to present complex data & analytics topics to stakeholders with various levels of literacy

Nice to have:

• Natural Language Processing (NLP) experience.

• Strong exploratory analysis skills.

• Experience working in a clinical organization is an asset.

Posting is closing 31st of March 2025. All submitted applications will be verified by us and assessed based on the objective criteria. Selected candidates will receive an invitation to introduce and present themselves using HireVue - a tool that allows to send answers to recruitment questions in the form of video recordings. On the final stage of the process, you will remotely meet the recruiting team consisting of representatives of a given department. At the end of April, we will announce a list of people for whom this year's internship program recruitment process was successful.

The internships will start in July and lasts 3 months.

We work in a hybrid scheme, be prepared to work partially office based. 

Don’t miss your opportunity! We are waiting for you!

Participation in the program does not guarantee employment after the internship.

Willing to know more? Any questions? Feel free to ask:

https://qr.short.az/Join_our_LinkedInGroup

AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.