As a Data Scientist you will:
- Apply your expertise in NLP/LLM to develop and refine models that address Roche business needs. Involved in building and fine-tuning models and optimising their performance to provide valuable insights and solutions to business stakeholders
- 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.
- 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.
- Provide methodical and implementation guidance as well as hands-on support around analytical LLM/NLP use cases. Evaluate the pros & cons of different NLP approaches and Generative AI platforms with comprehensive quantitative and qualitative analysis
- Communicate findings and market the value of use cases to key stakeholders.
- Contribute to positioning data science as a key competency within the enterprise
- Continuously look for opportunities to broaden knowledge, capabilities and skill set to enable talent to flow into different specialties.
- Be a role model for knowledge sharing within the DnA chapter.
- 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.
- Experience of working as a hands-on data scientist in pharmaceutical industry is preferred.
- Hands-on experience with Python programming and common NLP libraries (e.g., transformers, gensim, spaCy, etc.)
- Familiarity with essential frameworks (e.g. PyTorch) and infrastructure components (Docker, GPU) for training, fine-tuning and evaluating NLP tasks
- Experience in using both open source (e.g. HuggingFace) and closed source LLM models with different deep learning architectures
- Experience implementing RAG, working with knowledge databases and using LLM through APIs
- Good knowledge of effective training and optimising language models to fit for internal infrastructure and ensure seamless integration
- Familiarity with best practices for code generation, code documentation, data security, and compliance in cloud-based data science workflows.
- Proven experience to add value and insight by providing advanced analytical solutions.
- Data storytelling skills and using visualisation tools to communicate data and results with a non-technical audience.
- International, goal oriented mindset with can do attitude.
- Fluency in written and spoken English.