Job Title: MSAT Process Data Scientist Intern

• Location: EVolutive Facility (EVF) at 5 Tuas South Street 2, Singapore 639328

• Eligibility: credit bearing internship with 12 months duration preferably (6 months minimum)

• Others: Company transport provision at designated MRT Station

About you:

We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?

Sanofi Manufacturing and Supply Organization is preparing its future through an ambitious program named EVolutive Facility (EVF). The EVF Project is at the cornerstone of Sanofi strategy as it aims at creating a new manufacturing concept consisting of a new generation of evolutive multi-product facilities, modular, adaptable and agile, leveraging new disruptive technologies, to better address vaccine business challenges as well as Specialty Care biological products. One of these two EVF is implemented in Singapore in a new Greenfield site, with a design identical to the one in Neuville (France). Our manufacturing sites are state-of-the-art, powered by big data and digital. It is the bridge between scientific advances and transformative medicines and will be serving millions of people around the world.

Manufacturing Sciences, Analytics & Technology (MSAT) drives the industrialization and the improvement of biological processes and products. It embarks new technologies and digital trends. It is the keeper of manufacturing process knowledge. MSAT is at the crossroad of R&D and production. It is a multi-disciplinary function that provides expertise in process, manufacturing sciences, process modeling, statistical analysis, process validation and technology transfer.

The MSAT team in Sanofi EVF, Singapore is seeking an intern or trainee as MSAT Process Data Scientist to help setup the framework and systems of bioprocess data in a greenfield facility. This position will connect the digital infrastructure with the upstream and downstream process engineers, to enable a simple user interface to compare discrete and continuous process data, potentially across different manufacturing sites. The Process Data Scientist intern/trainee should design/execute the framework and systems to enable lifecycle management including routine user training, user access and troubleshooting.

This position reports into EVF Singapore MSAT team, with heavy direction and guidance from the Data Science & Digital (DSD) team based in France.

Main responsibilities:

• Understand the setup and capabilities of the site’s data integration layer and plant connectivity with the goal of designing and setting up bioprocess data framework and system.

• Combine expertise in biotechnological processes to ensure technical propositions are in accordance with Good Manufacturing Practices (GMP) and industrial constraints to maximize robustness, reliability and economics.

• Work with cross-functional stakeholders (including MSAT DSD and MSAT process engineers) to design and setup framework and systems to collate, manage, visualize and analyze bioprocess data.

• Translate process data to enable end-users (process engineers) to visualize data for process performance and trending, as well as to perform data analysis using in house statistical tools/softwares

• Work closely with MSAT DSD and MSAT process teams to analyse the real time process data to to improve process monitoring and control.

• Adheres to the work and governance frameworks and deliver in a timely manner.

About you:

• Holds or is working to complete a scientific or engineering degree (or higher), preferably in Biotechnology, Biological Sciences, or Chemical Engineering.

• Is data-driven, scientifically curious and an effective communicator.

• Ideally has work (or internship) experience in a cGMP biopharmaceutical facility, and/or small- or pilot-scale hands-on experience with mammalian cell culture and purification techniques.

• Is familiar with data analytics and an experience in using data analytics tools would be advantageous such as R, JMP, Python, Matlab.

• Has experience with developing business requirements, use cases and user stories in a data analytics context.