Senior Health Data Scientist
1 week geleden
We are seeking a highly skilled Senior Health Data Scientist to join our team at the Danone Nutricia Research & Innovation Center in Utrecht, the Netherlands.
Key Responsibilities- Develop state-of-the-art solutions using advanced statistical and data science techniques.
- Analyze high-dimensional data in clinical studies, applying advanced statistics and machine learning, conduct post-hoc analyses, reuse historical data and perform meta-analysis/systematic reviews to inform evidence-based decision-making.
- Leverage Real-World Data (RWD): Analyze high-dimensional health datasets collected from digital health tools via real-world/pragmatic or clinical study settings.
- Co-build evidence generation programs: Collaborate with colleagues to design and implement evidence generation programs. Contribute to the strategic direction by aligning initiatives with scientific roadmaps.
- Strategic Execution: Understand and actively execute the scientific strategy within efficient project contributions. Ensure timely and high-quality execution of projects and programs.
- Data-Driven Impact: Leverage advanced statistical and machine learning models to extract insights from multidimensional data obtained from clinical studies. Efficiently collate, process, and analyze real-world data to create and validate new nutritional engines. Application validation of Digital Health tools, including setting quality criteria and defining in which settings a tool can be used.
- Cross-Functional Collaboration: Work closely with cross-functional teams, including Life Science, Digital Health, Biometrics, Data Science, Clinical Operations, and Medical Affairs. Provide expert data science and statistical input to enhance decision-making.
- Innovation: Contribute to the development of new data science innovations. Play a pivotal role in shaping the future of nutritional products through evidence-based insights.
- You hold a degree in a relevant field.
- 3-5 years of experience in the data science combined with life science/clinical domain.
- Prior experience in leading programs and contributing to strategy, able to work independently.
- Statistical and Data Science Proficiency: A thorough experience in advanced statistical and machine learning methods in the health domain. Eager to bring innovation in clinical research, including high-dimensional data, secondary use of clinical data (historical data, systematic reviews), Real-World Data/Real-World Evidence (RWD/RWE), application validation of digital tool data in clinical trials. Expert in programming languages R and Python, coding standards, best practices, and data standards, cloud-based IT systems & databases.
- Quality and Purpose: You've navigated good clinical practices and quality management systems. Driven by purpose, you're committed to contributing to Danone's mission of positively impacting health. Your excellent communication skills in English ensure seamless collaboration.
At Danone, we offer a complete package of benefits, with a competitive primary salary and yearly bonus, but also benefits like a premium free pension, 30 days annual leave and several discounts on a collective health insurance and even on some of our products. In the Netherlands we also offer a hybrid working environment which enables each team to meet our people's desire for flexibility. Across our 3 office hubs in Hoofddorp, Rijswijk and Utrecht this helps us create better opportunities for connection & synergies across our entities, teams, functions and categories.
Hit the "apply now" button. After your application deadline first feedback will follow within 2 weeks. In case you are invited to the selection process you should expect to receive feedback 2 weeks after each step of the process
To comply with GDPR regulations, we cannot process your personal data without given consent. Therefore, we strongly recommend applying directly via our website.
Need more information? Please contact Valerija Usova, Talent Manager via >
All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.
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