Senior Data Scientist

Qualifications

• Master’s or PhD in AI, Machine Learning, Computer Engineering, or Applied Math.
• 5+ years of experience in AI/ML strategy, leadership, and delivery.
• Proven ability to build and scale enterprise-level AI/LLM platforms.

Technical & Strategic Requirements

• Strategic AI Leadership:

o Defines and drives AI roadmaps aligned with corporate goals.

o Oversees model lifecycle from experimentation to production.

• LLM & NLP (Architect Level):

o Designs LLM-based ecosystems with RAG pipelines, model orchestration, and fine-tuning strategies.

o Leads fine-tuning or domain-specific pretraining using proprietary datasets.

o Integrates Azure OpenAI, AWS Bedrock, Anthropic Claude, or Google Vertex AI into enterprise stacks.

o Defines governance, compliance, and security standards for LLM deployments.

o Oversees evaluation frameworks for hallucination rate, factual accuracy, and toxicity control.

• Infrastructure & Governance:

o Owns data governance policies, feature stores, and model observability infrastructure.

o Collaborates with DevOps and Security to ensure scalability and resilience.

• Team & Stakeholder Leadership:

o Builds and manages multidisciplinary AI teams (Data Scientists, ML Engineers, Data Engineers).