L4-Data Science-CRL

As a Senior Data Scientist, your primary responsibilities include:

•  Lead end-to-end data science initiatives, including data exploration, model development, validation, implementation, and support for mission-critical applications.
• Collaborate closely with cross-functional data teams to automate data science pipelines and integrate models into business workflows and digital platforms.
• Partner with business units in a consultative and collaborative manner, advising on the most effective approaches to leverage data science and Generative AI technologies to deliver innovative, high-impact solutions.

Key Elements

We are looking for the following minimum qualifications for this role:

• Master’s with a minimum of 5 years’ experience or Bachelor’s with a minimum of 7 years’ experience in Data science, Computer science, Statistics, Operations research, applied mathematics, applied physics or any related field;
• Excellent analytical and problem-solving skills with the ability to approach challenges creatively
• Strong communication skills to translate the findings into actionable business recommendations through rich data visualization;
• Familiar with Agile methodologies and tools;
• Self-driven and capable of working both independently and collaboratively within a team setting.
• Experience in or strong understanding of the life science industry, particularly in leveraging data science to support operational excellence, is preferred.

Technical Expertise required:

• Minimum of 5 years’ hands-on experience processing, analyzing and modeling large and complex data sets.
• Minimum of 3 years’ experience with the full Machine Learning product lifecycle, with a demonstrated ability to take initiative and ensure proactive delivery of project milestones.
• Minimum of 5 years’ experience working with development toolsets such as SQL, PySpark, Python, Pandas or Scala.
• Experience with Generative AI technologies for scientific document reading, summarization, and generation, including prompt engineering, retrieval pipelines, and LLM fine-tuning for domain-specific applications.