Data Scientist

Experience:

• Junior Level: 4+ years
• Senior Level: 8+ years

Work Mode: Remote

About the Role:

We are seeking a highly skilled and motivated Data Scientist with deep expertise in Machine Learning (ML), Deep Learning, and Large Language Models (LLMs) to join our forward-thinking AI & Data Science team. This is a unique opportunity to contribute to real-world impact in the healthcare industry, transforming the way patients and providers interact with health data through Generative AI and NLP-driven solutions.

Key Responsibilities:

• LLM Development & Fine-Tuning:
• Fine-tune and customize LLMs (e.g., GPT, LLaMA2, Mistral) for use cases such as text classification, NER, summarization, Q&A, and sentiment analysis.
• Experience with other transformer-based models (e.g., BERT) is a plus.
• Data Engineering & Pipeline Design:
• Collaborate with data engineering teams to build scalable, high-quality data pipelines for training/fine-tuning LLMs on structured and unstructured healthcare datasets.
• Experimentation & Evaluation:
• Design rigorous model evaluation and testing frameworks (e.g., with tools like TruLens) to assess performance and optimize model outcomes.
• Deployment & MLOps Integration:
• Work closely with MLOps teams to ensure seamless integration of models into production environments on cloud platforms (AWS, Azure, GCP).
• Predictive Modeling in Healthcare:
• Apply ML/LLM techniques to build predictive models for use cases in oncology (e.g., survival analysis, risk prediction, RWE generation).
• Cross-functional Collaboration:
• Engage with domain experts, product managers, and clinical teams to translate healthcare challenges into actionable AI solutions.
• Mentorship & Knowledge Sharing:
• Mentor junior team members and contribute to the growth of the team’s technical expertise.

Qualifications:

• Master’s or Doctoral degree in Computer Science, Data Science, Artificial Intelligence, or related field.
• 5+ years of hands-on experience in machine learning and deep learning, with at least 12 months of direct work on LLMs.
• Strong coding skills in Python, with experience in libraries like HuggingFace Transformers, spaCy, NLTK, TensorFlow, or PyTorch.
• Experience with prompt engineering, RAG pipelines, and evaluation techniques in real-world NLP deployments.
• Hands-on experience in deploying models on cloud platforms (AWS, Azure, or GCP).
• Familiarity with the healthcare domain and working on Real World Evidence (RWE) datasets is highly desirable.

Preferred Skills:

• Strong understanding of healthcare data regulations (HIPAA, PHI handling, etc.)
• Prior experience in speech and text-based AI applications
• Excellent communication and stakeholder engagement skills
• A passion for impactful innovation in the healthcare space