Data Scientist

We are seeking an experienced Data Scientist with a proven track record in Machine Learning, Deep Learning, and a demonstrated focus on Large Language Models (LLMs) to join our cutting-edge Data Science team. You will play a pivotal role in developing and deploying innovative AI solutions that drive real-world impact to patients and healthcare providers.

• LLM Development and Fine-tuning: fine-tune, customize, and adapt large language models (e.g., GPT, Llama2, Mistral, etc.) for specific business applications and NLP tasks such as text classification, named entity recognition, sentiment analysis, summarization, and question answering. Experience in other transformer-based NLP models such as BERT, etc. will be an added advantage.
• Data Engineering: collaborate with data engineers to develop efficient data pipelines, ensuring the quality and integrity of large-scale text datasets used for LLM training and fine-tuning.
• Experimentation and Evaluation: develop rigorous experimentation frameworks to evaluate model performance, identify areas for improvement, and inform model selection. Experience in LLM testing frameworks such as Tru Lens will be an added advantage.
• Production Deployment: work closely with MLOps and Data Engineering teams to integrate models into scalable production systems.
• Predictive Model Design and Implementation: leverage machine learning/deep learning and LLM methods to design, build, and deploy predictive models in oncology (e.g., survival models).
• Cross-functional Collaboration:
  
  partner with product managers, domain experts, and stakeholders to understand business needs and drive the successful implementation of data science solutions.
• Knowledge Sharing: mentor junior team members and stay up to date with the latest advancements in machine learning and LLMs.

• Doctoral or master’s degree in computer science, Data Science, Artificial Intelligence, or related field.
• 5+ years of hands‑on experience in designing, implementing, and deploying machine learning and deep learning models.
• 12+ months of in-depth experience working with LLMs. Proficiency in Python and NLP‑focused libraries (e.g., spaCy, NLTK, Transformers, Tensor Flow/PyTorch).
• Experience working with cloud‑based platforms (AWS, GCP, Azure).

• Excellent problem‑solving and analytical abilities.
• Strong communication skills, both written and verbal.
• Ability to thrive in a collaborative and fast‑paced environment.