Takeda

PrincipalDataScienceAnalyst

€4k+ Bratislava, Slovakia FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Principal Data Science Analyst at Takeda. Skills: AI/ML strategy, MLOps, data science leadership. design and implement the AI/ML strategy across Manufacturing Sciences. design AI/ML roadmaps”

What You'll Achieve.

deliver measurable operational impact; support Manufacturing Sciences decision-making and operational goals

What They're Looking For.

Must Have

Master's or Ph. D. in Data Science, CS, Engineering, or related STEM, 10+ years in AI/data science roles, Advanced ML/AI expertise experience (Classical ML: KNN, SVM, Random Forest/GBMs etc.), Deep learning: CNNs/RNNs/GRU, autoencoders, Backprop/Autodiff, experience with MLOps at scale, programming skills (Python, SQL), familiarity with distributed computing (Spark, Kubernetes)

Nice to Have

Ph. D., Experience with pharma, biotech, or chemical manufacturing datasets, Familiarity with workflow automation/orchestration tools (Airflow, n8n), cloud deployment (Docker, Kubernetes, Azure ML, AWS Sagemaker), Experience in regulated environments, specifically: pharma preferred

What You'll Do.

design and implement the AI/ML strategy across Manufacturing Sciences

design AI/ML roadmaps

drive adoption of advanced analytics

mentor data scientists

influence analytics direction across Manufacturing Sciences

shape manufacturing AI/ML strategy

lead cutting-edge projects

Lead global AI/ML initiatives across 20+ manufacturing facilities

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

and regulatory compliance

Translate emerging AI/ML trends into practical applications

How You'll Work.

Team & Collaboration

working in close partnership with Manufacturing Sciences domain leaders; collaborate with Manufacturing Sciences SMEs, IT, engineering and quality business functions

Full Job Description

By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s [Privacy Notice](https://jobs.takeda.com/privacynotice) and [Terms of Use](https://www.takeda.com/terms-and-conditions/). I further attest that all information I submit in my employment application is true to the best of my knowledge. ## **Job Description** **The Future Begins Here** : At Takeda, we are creating a future-ready organization that uses data and digital to meet the needs of patients, our people, and the planet. We need your help to make this happen. Join our **Innovation Capability Center (ICC)** in Bratislava, Slovakia. **At Takeda’s ICC we Unite in Diversity:** Takeda is committed to creating an inclusive and collaborative workplace, where individuals are recognized for their backgrounds and the abilities they bring to our company. We are continuously improving our collaborators’ journey in Takeda, and we welcome applications from all qualified candidates. Here, you will feel welcomed, respected, and valued as an important contributor to our diverse team. **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 priorit

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