Senior Data Scientist and Solution Architect

Reposted 26 Days Ago
Be an Early Applicant
Bangalore, Bengaluru Urban, Karnataka, IND
In-Office
Senior level
Cloud • Information Technology • Internet of Things • Professional Services • Software
The Role
Lead architecture and development of production AI/ML solutions for supply chain problems. Build and deploy LLM-powered apps, RAG pipelines, agentic workflows, and predictive models. Provide technical leadership, mentorship, experimental rigor, and cross-functional delivery while ensuring model governance, interpretability, and business impact.
Summary Generated by Built In

Meet the Team 

We are the Supply Chain Transformation AI Team within Cisco’s Supply Chain Operations. We are a diverse, fast-moving group of AI engineers and data scientists who collaborate directly with Product Operations. We don’t just analyze data; we transform it into actionable intelligence. By building advanced AI solutions, we empower our NPI (New Product Introduction) PMs, Product, and Test Engineering teams to anticipate market shifts, optimize workflows, and meet the evolving demands of our product lifecycle.

Your Impact 

You will lead the architectural direction and development of high-impact AI/ML solutions, transforming complex, ambiguous supply chain challenges into measurable business outcomes.

Core Responsibilities

  • 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.

Minimum Qualifications

  • 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.
  • Generative AI & LLM Proficiency
    • 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.

Preferred Qualifications

  • 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.

Why Cisco? 

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere. 

We are Cisco, and our power starts with you. 


Disclaimer

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.


Skills Required

  • Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or related quantitative field
  • 7-10 years professional experience in data science, analytics, or related discipline
  • Proven expertise in statistical analysis, correlation analysis, and advanced statistical techniques
  • Hands-on experience building and deploying LLM-powered applications in production
  • Experience with Agentic AI systems, autonomous workflows, tool calling, and multi-agent orchestration
  • Knowledge of MCP (Model Context Protocol), A2A 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 knowledge of supervised/unsupervised learning, time-series analysis, and optimization techniques
  • Experience in fine-tuning LLMs and evaluating AI systems (eval frameworks, human-in-the-loop validation)
  • Expert-level proficiency in Python (Pandas, Scikit-learn, PyTorch/TensorFlow) and SQL
  • Familiarity with modern data engineering tools (Spark, Snowflake, or similar)
  • Ability to design end-to-end data pipelines feeding production AI systems
  • Exceptional communication skills to translate analytical findings for non-technical stakeholders
  • Self-driven, strong problem-solving, ability to manage multiple priorities in fast-paced environment
  • Master's or PhD in related field
  • Proven track record deploying models that influenced supply chain or operational efficiency
  • Experience with MLOps practices (MLflow, Kubeflow, or similar)
  • Experience working with large-scale unstructured and multi-modal datasets

Cisco Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cisco and has not been reviewed or approved by Cisco.

  • Healthcare Strength Health coverage is described as robust with multiple plan options and access to onsite/virtual LifeConnections Health Centers on major campuses. Company materials also highlight mental-health resources and comprehensive preventive care, supporting strong core medical benefits.
  • Leave & Time Off Breadth Time away includes company‑wide recharge days, a paid birthday, a year‑end shutdown, and paid Critical Time Off for emergencies. Paid volunteer days further expand opportunities to step away and recharge.
  • Parental & Family Support Policies include a global minimum for paid parental leave for primary caregivers, caregiving concierge services, and on‑site children’s learning centers in select locations. In the U.S., family‑building support is consolidated under Carrot with a defined lifetime maximum, indicating structured assistance across fertility, preservation, adoption, and surrogacy.

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The Company
HQ: San Jose, CA
77,500 Employees
Year Founded: 1984

What We Do

Cisco (NASDAQ: CSCO) enables people to make powerful connections--whether in business, education, philanthropy, or creativity. Cisco hardware, software, and service offerings are used to create the Internet solutions that make networks possible--providing easy access to information anywhere, at any time. Cisco was founded in 1984 by a small group of computer scientists from Stanford University. Since the company's inception, Cisco engineers have been leaders in the development of Internet Protocol (IP)-based networking technologies. Today, with more than 71,000 employees worldwide, this tradition of innovation continues with industry-leading products and solutions in the company's core development areas of routing and switching, as well as in advanced technologies such as home networking, IP telephony, optical networking, security, storage area networking, and wireless technology. In addition to its products, Cisco provides a broad range of service offerings, including technical support and advanced services. Cisco sells its products and services, both directly through its own sales force as well as through its channel partners, to large enterprises, commercial businesses, service providers, and consumers.

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