Graduate Data Scientist – Digital Transformation (Ringaskiddy)

Pfizer; Ringaskiddy; Vor Ort; EUR 30.000 - 42.000; Vollzeit

Benefits dieser Stelle

Healthcare

Pension

Share scheme

Shuttle service

Accommodation support

Zusammenfassung

Pfizer Ringaskiddy in Cork invites applications for a Graduate Data Scientist within the Innovation & Launch Sciences function. The two-year programme combines induction, mentoring, and CPD modules while you help deliver the site's digital transformation through data analytics and process improvements.

You will collaborate with cross-functional teams, build data models, and support manufacturing intelligence initiatives to accelerate drug discovery and manufacturing efficiency.

Qualifikationen

• Be completing or just completed an honours Degree or MSc in Mathematical Science / Data Science / Data Analytics.
• Strong experience in statistics, analytics methods and programming languages (VB, SQL, R, Python).
• Willingness to learn and be challenged; GMP familiarity preferred.
• UI/UX design knowledge and Lean/Six Sigma understanding.

Aufgaben

• One-year induction programme.
• Structured mentoring & coaching – objective setting during each assignment.
• Attend management training programmes.
• CPD 6 module professional training programme.
• Lead and support data science projects.
• Deliver routine statistical support to ensure continued compliance with cGMPs.

Kenntnisse

Statistical tools

SQL

Python

R

Visual Basic

Data analytics

Ausbildung

Honours degree / MSc in Data Science

Tools

UI/UX Knowledge

Jobbeschreibung

Pfizer Ringaskiddy in Cork invites applications for a Graduate Data Scientist within the Innovation & Launch Sciences function. The two-year programme combines induction, mentoring, and CPD modules while you help deliver the site's digital transformation through data analytics and process improvements.

You will collaborate with cross-functional teams, build data models, and support manufacturing intelligence initiatives to accelerate drug discovery and manufacturing efficiency.