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The Position
As a Data Scientist, you will join the data science cluster in the Roche Informatics Data and Analytics Chapter (DnA). You will be part of one or several multi-disciplinary agile teams where you'll actively shape the future of healthcare by using data science methods and principles to generate deeper insights from a great variety of data sources.
To achieve this, you will proactively identify needs, design and implement analytical solutions, provide advice and consulting support to our key stakeholders and show impact by executing proof-of-value initiatives, or contributing to existing products.
As a Data Scientist you will:
1. Be accountable for the development and implementation of Data Science products focusing on Natural Language Processing leveraging LLMs and Generative AI tools.
2. Support proactive identification of the most relevant LLM/NLP use cases in collaboration with key stakeholders.
3. Apply your expertise in NLP/LLM to develop and refine models that address Roche business needs.
4. Be involved in building and fine-tuning models and optimising their performance to provide valuable insights and solutions to business stakeholders.
5. Support prioritisation efforts, understand feasibility and business impact, take smart risks to make informed decisions in a fast-paced, evolving environment to deliver patient benefits faster.
6. Collaborate within global agile teams in the Roche Informatics business and foundational domains to develop products that provide the highest value to both Roche Pharma and Diagnostics business stakeholders.
7. Provide methodical and implementation guidance as well as hands-on support around analytical LLM/NLP use cases.
8. Evaluate the pros & cons of different NLP approaches and Generative AI platforms with comprehensive quantitative and qualitative analysis.
9. Communicate findings and market the value of use cases to key stakeholders.
10. Contribute to positioning data science as a key competency within the enterprise.
11. Continuously look for opportunities to broaden knowledge, capabilities and skill set to enable talent to flow into different specialties.
12. Be a role model for knowledge sharing within the DnA chapter.
13. Act as a coach, mentor, or buddy to help colleagues grow and develop.
Qualifications:
M.Sc. or PhD in Computer Science, Physics, Statistics, Mathematics or equivalent degree and experience with machine learning/data mining/artificial intelligence.
At least 5 years of hands-on experience as a Data Scientist.
Hands-on experience with Python programming and common NLP libraries (e.g., transformers, gensim, spaCy, etc.).
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