Role descriptionData Science Lead Experience Level: 8-12 Years
Role SummaryTechnical leader responsible for driving complex ML, NLP, and LLM initiatives. Owns solution architecture, quality standards, and technical direction while mentoring teams and advising stakeholders.
Key Responsibilities- Lead large-scale data science and ML programs.
- Define NLP and LLM solution approach and architecture.
- Set standards for model evaluation, monitoring, and governance.
- Guide teams on best practices across ML lifecycle.
- Advise business and leadership on ML strategy and feasibility.
- Stay current on emerging ML and LLM technologies.
Mandatory / Key Skills (with expected experience)- Advanced Python and ML systems design: 8-12 years
- End-to-end ML delivery in production environments: 8-12 years
- NLP for enterprise-scale use cases: 6-8 years
- LLM ecosystem (design choices, evaluation, trade-offs): 5-7 years
- Model evaluation, monitoring, and risk management: 6-8 years
- Cloud-native ML architectures: 5-7 years
- Technical leadership and stakeholder communication: 6-8 years
EducationBachelor's / Master's / PhD in Computer Science, Data Science, Engineering, or related field.
Process & Ways of Working- Strong understanding of SDLC, Agile, and Scrum methodologies.
- Ability to gather requirements, create technical designs, and write clear documentation.
- Participate in code reviews and ensure best engineering practices.
Behavioral & Soft Skills- Excellent problem-solving and analytical thinking.
- Strong communication and collaboration skills across cross-functional teams.
- Self-driven, adaptable, and eager to learn new technologies.
