Data Scientist Team Lead

The Opportunity

As the Data Scientist Team Lead, you will oversee and guide our data science team, driving the development and deployment of advanced machine learning models, with a particular emphasis on Natural Language Processing (NLP). Your responsibilities will include managing and optimizing our Natural Language Understanding (NLU) models, leading prompt engineering efforts for Large Language Models (LLMs), and conducting thorough NLP assessments. You will also ensure the continuous monitoring and refinement of these models to maintain peak performance. These models will be seamlessly integrated into our core products, playing a critical role in advancing our strategic objectives.

Who You Are

You are a tech enthusiast who thrives in innovative environments. You have a deep passion for NLP, AI, and Machine Learning, with the vision to apply these technologies to solve real-world challenges in healthcare. You are a strong leader with a proven track record of managing and scaling data science teams, and you’re excited about working on solutions that have a positive, global impact.

What You’ll Do

• Manage Data Science Team
• Responsibility of Fullstack DS from development to production
• Performing multiple assignments for Natural Language Processing (NLP)
• Responsibilities over Natural Language Understanding (NLU) models
• Developing and implementing machine learning models in a production environment
• Handling prompt engineering tasks
• Monitoring and optimizing models

Qualifications

• BSc in Engineering, Computer Science, Mathematics, Physics or a related field from a University. MSc is an advantage
• At least 2-3 years of hands-on experience as an NLP Data Scientist
• Experience developing with LLMs - Prompt engineering, fine-tuning, deployment considerations
• At least 2 years of managing a data science team
• Hands-on coding experience in Python is a must, with expertise in ML frameworks (e.g. Transformers) and data processing libraries (e.g. Pandas) -
• Basic knowledge and experience in ML-Ops is a must
• Basic knowledge and experience in SQL DBs