Data Scientist

Who You’ll Work With

Minimum Qualifications

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science , or a related quantitative discipline.
• 7–10+ years of professional experience in Data Science, Advanced Analytics, Machine Learning, or a related field.
• Strong experience applying statistical analysis, correlation analysis, and advanced statistical techniques to solve business problems.
• Expert-level proficiency in Python and SQL .
• Strong understanding of supervised and unsupervised machine learning, time-series analysis, and optimization techniques .
• Hands-on experience developing and deploying AI/ML models and LLM-powered applications in production environments.
• Experience with Agentic AI, autonomous workflows, tool calling, or multi-agent orchestration .
• Experience building RAG pipelines, semantic retrieval systems, embeddings, vector databases, and AI evaluation frameworks .
• Strong prompt engineering skills, including prompt design, structured outputs, guardrails, and workflow optimization.
• Experience designing end-to-end data pipelines that support production AI/ML systems.
• Experience with MLOps and model lifecycle management .
• Proven ability to translate complex analytical findings into actionable business insights.
• Strong problem-solving, communication, collaboration, and stakeholder-management skills.

Preferred Qualifications

• Experience applying AI/ML and advanced analytics to supply chain, manufacturing, semiconductor, or operational environments .
• Hands-on experience with MCP (Model Context Protocol), A2A (Agent-to-Agent) communication patterns, and agent integration frameworks .
• Experience with LLM fine-tuning, human-in-the-loop validation, and AI evaluation frameworks .
• Experience with modern data platforms such as Snowflake or equivalent technologies.
• Experience working with large-scale unstructured and multi-modal datasets .
• Proven track record of deploying AI/ML models that have directly improved supply chain performance, operational efficiency, forecasting, planning, or decision-making .
• Experience with graph analytics, optimization, predictive modeling, and advanced forecasting .
• Strong understanding of responsible AI, model governance, explainability, and bias mitigation.
• Experience working in global, cross-functional organizations and fast-paced technology environments.

Why Cisco?

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