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Data scientist iii (pavia)

Pavia
Thermo Fisher Scientific
Data scientist
Pubblicato il 13 maggio
Mansioni della posizione
Work Schedule
Standard (Mon-Fri)
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Office
DESCRIPTION:
Join our team at Thermo Fisher Scientific as a Data Scientist III within the Data Science Center of Excellence. In this role, you will contribute to improving business efficiency and decision-making across the enterprise by developing and deploying data-driven insights and solutions.
Working at the intersection of business and technology, you will partner with cross-functional teams to understand business needs, perform advanced analytics, and deliver scalable machine learning and AI solutions. You will apply techniques such as machine learning, natural language processing, and statistical modeling to solve complex commercial and operational challenges, including generating actionable recommendations delivered through platforms like Salesforce.
This role offers the opportunity to work with modern data platforms and cloud technologies (Databricks, AWS), contribute to production-grade data science solutions, and drive measurable business impact. The ideal candidate combines strong technical expertise, solid business acumen, and the ability to translate analytical outputs into clear, actionable insights.
Key Responsibilities
Commercial Analytics & Solution Development
- Design, develop, and validate predictive models, optimization algorithms, and recommendation systems
- Translate business problems into analytical approaches that drive measurable outcomes (e.g., revenue growth, conversion rates, operational efficiency)
- Develop scalable, interpretable, and actionable insights and recommendations for business stakeholders
- Partner with Sales, Marketing, Commercial Operations, Product, and IT to refine use cases and support adoption
- Apply statistical analysis, experimental design, and hypothesis testing to evaluate performance and impact

Technical Execution & Data Engineering Collaboration
- Build, train, and deploy machine learning models using Python-based tools (e.g., scikit-learn)
- Wo
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