Job Description
Job Overview
At Charles River Laboratories, we’re transforming how we work by harnessing the power of AI, data, and digital innovation to accelerate the discovery and development of life-saving therapies. Our vision is to embed AI and advanced analytics across every stage of our scientific and operational workflows, empowering our teams with smarter tools, seamless data, and actionable insights to deliver client-centric services and solutions that better serve our customers and, ultimately, improve patients’ lives.
As a Senior Data Scientist and a member of our Enterprise Data & Analytics engineering team, you will play a pivotal role in this transformation. You’ll lead the design, development, and deployment of data-driven and AI-powered solutions that enhance customer value, streamline operations, and create meaningful, data-informed experiences for our employees. Through advanced analytics and generative AI, you’ll help Charles River unlock new possibilities in how we deliver science, innovation, and impact to our clients and the patients they serve.
In this role, 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.
Job Description
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:
- 5+ years’ hands-on experience processing, analyzing and modeling large and complex data sets;
- 3+ years’ experience with the full Machine Learning product lifecycle, with a demonstrated ability to take initiative and ensure proactive delivery of project milestones;
- 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.