Senior Data Scientist and Solution Architect

• Strategic Architecture: Translate high-level business objectives into scalable, rigorous data science projects.
• Advanced AI/ML Development: Architect and deploy sophisticated models, including predictive analytics, LLM-powered applications, and agentic workflows.
• Technical Leadership: Drive methodological rigor in experimental design, model evaluation, and statistical validation.
• Cross-Functional Execution: Partner with AI Engineers to ensure seamless integration from research to production.
• Innovation & Research: Pilot cutting-edge methodologies (e.g., Agentic Framework, RAG, fine-tuning, graph analytics) to maintain a competitive edge.
• Mentorship & Governance: Foster a culture of technical excellence and code reproducibility while ensuring all models adhere to enterprise ethics, bias mitigation, and interpretability standards.

• Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative field.
• Minimum of 7-10 years of professional experience in data science, analytics, or a related discipline, with demonstrated expertise in statistical analysis
• Proven track record of applying correlation analysis and advanced statistical techniques in a business context.
• Strong problem-solving skills, attention to detail, self-driven, and ability to manage multiple priorities in a fast-paced environment.

•

• Hands-on experience building and deploying LLM-powered applications in production
• Experience with Agentic AI systems, autonomous workflows, tool calling, and multi-agent orchestration
• Strong understanding of MCP (Model Context Protocol), A2A (Agent-to-Agent) communication patterns, and agent integration frameworks
• Experience building RAG pipelines including embeddings, retrieval strategies, reranking, context management, and evaluation
• Strong prompt engineering skills including prompt design, structured outputs, guardrails, and workflow optimization
• Experience working with vector databases and semantic retrieval systems
• Advanced Statistical & ML Expertise: Deep understanding of supervised/unsupervised learning, time-series analysis, and optimization techniques.
• Experience in fine-tuning LLMs, advanced prompt engineering, and evaluating AI systems (eval frameworks, human-in-the-loop validation).

• Programming & Data Stack: Expert-level proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow) and SQL. Familiarity with modern data engineering tools (Spark, Snowflake, or similar).
• System Design: Ability to design end-to-end data pipelines that feed into production AI systems.
• Communication: Exceptional ability to distill complex analytical findings into actionable business insights for non-technical stakeholders.

• Master’s or PhD in Data Science, Statistics, Computer Science, or related quantitative field.
• Proven track record of deploying models that have directly influenced supply chain or operational efficiency.
• Experience with MLOps practices (MLflow, Kubeflow, or similar) to manage the model lifecycle.
• Experience working with large-scale, unstructured datasets and multi-modal data.

To ensure that we hire the best talent in the right way, we follow a strict hiring process and recently, Cisco has been made aware of fraudulent recruiters claiming to be from the company. Please be advised that any communication from Cisco about careers will:

• 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

Cisco will never make a job offer without conducting an interview process or ask you for money in any way. If you have been requested to apply for a role or have received an offer from a site other than https://careers.cisco.com or cisco.wd5.myworkday.com , do not provide any personal identifying information, including your Aadhaar or other personal identifying number, birth certificate, banking information, driver's license, or passport.

If you are the target of a recruiting scam, consider filing a report with your local law enforcement authorities. Cisco bears no responsibility, and cannot be held liable, for any claims, damages, expenses, or other inconvenience resulting from or in any way connected to recruiting scams.