Data Scientist
About the role
Meet the Team
Components (Silicon and Optical) supply chains
business architecture, advanced data science, AI, analytics, and program management
Your Impact
Data Scientist
AI/ML solutions
Generative AI, LLM, and Agentic AI
You will
- Translate complex business objectives into scalable and rigorous
data science and AI/ML solutions
.
- Develop and deploy advanced AI/ML models, including
predictive analytics, LLM-powered applications, and Agentic AI workflows
.
- Apply advanced statistical methods, experimental design, model evaluation, and statistical validation to ensure methodological rigor.
- Build solutions using
supervised and unsupervised learning, time-series analysis, optimization, and statistical modeling
.
- Design and develop
RAG pipelines
, including embeddings, retrieval strategies, reranking, context management, and evaluation.
- Develop and optimize
LLM-powered applications
, including prompt engineering, structured outputs, guardrails, and workflow optimization.
- Explore emerging AI methodologies such as
Agentic AI, multi-agent orchestration, tool calling, graph analytics, and LLM fine-tuning
.
- Partner with AI Engineers and technology teams to transition data science solutions from experimentation into production.
- Design end-to-end
data pipelines and AI solutions
that are scalable, reliable, and production-ready.
- Work with large-scale structured, unstructured, and multi-modal datasets to generate actionable insights.
- Apply
MLOps practices
to support model deployment, monitoring, lifecycle management, and continuous improvement.
- Drive innovation by evaluating emerging AI/ML technologies and identifying opportunities to apply them to supply chain challenges.
- Ensure solutions follow enterprise standards for
responsible AI, ethics, bias mitigation, interpretability, and reproducibility
.
- Communicate complex analytical findings clearly and translate them into actionable recommendations for business and non-technical stakeholders.
- Mentor team members and contribute to a culture of technical excellence, collaboration, and continuous learning.
Who You’ll Work With
Minimum Qualifications
- Bachelor’s degree in
Statistics, Mathematics, Computer Science, Data Science
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?
Disclaimer
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- be in direct response to an application you have submitted through the company career site
- begin with screening or an interview
- originate from a Cisco email address, and
- be conducted across email, phone, or WebEx
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Not included in the source posting: benefits.
Skills
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