Senior Data Scientist

Senior Data Scientist

Takeda

Bratislava, Slovakia

THE OPPORTUNTY

We are seeking a Principal Data Science Analyst to design and implement the AI/ML strategy across Manufacturing Sciences, working in close partnership with Manufacturing Sciences domain leaders to translate strategic priorities into scalable and compliant solutions. You will design AI/ML roadmaps, drive adoption of advanced analytics, and mentor data scientists, and influence analytics direction across Manufacturing Sciences to deliver measurable operational impact. You will also shape manufacturing AI/ML strategy, lead cutting-edge projects, and directly impact global manufacturing operations in a collaborative, innovative environment.

RESPONSIBILITIES

• Lead global AI/ML initiatives across 20+ manufacturing facilities in alignment with Manufacturing Sciences strategic priorities;
• Architect AI platforms integrating real-time manufacturing data with cloud MLOps environments;
• Drive innovation in AI/ML manufacturing optimization and autonomous process control;
• Establish standards for model governance, bias mitigation, and regulatory compliance;
• Mentor data scientists and collaborate with Manufacturing Sciences SMEs, IT, engineering and quality business functions;
• Translate emerging AI/ML trends into practical applications that support Manufacturing Sciences decision-making and operational goals.

SKILLS AND QUALIFICATIONS

Education Requirements

• Master’s or Ph.D. in Data Science, CS, Engineering, or related STEM;
• 5+ years in AI/data science roles, including demonstrated technical and people leadership;
• Advanced ML/AI expertise experience (Classical ML: KNN, SVM, Random Forest/GBMs etc.). Deep learning: CNNs/RNNs/GRU, autoencoders, Backprop/Autodiff and experience with MLOps at scale;
• Strong programming skills (Python, SQL) and familiarity with distributed computing (Spark, Kubernetes);
• Experience in regulated environments, specifically: pharma preferred.

Desired Skills

• Experience with pharma, biotech, or chemical manufacturing datasets;
• Familiarity with workflow automation/orchestration tools (Airflow, n8n) and cloud deployment (Docker, Kubernetes, Azure ML, AWS Sagemaker).