Senior Data Scientist

Capgemini • Seattle, WA

3d • $101,140 - $182,624

About The Position

Capgemini is hiring a Senior Data Scientist to define and deliver AI strategy and architecture for telecom network engineering, operations, automation, and digital transformation. The role requires deep expertise in wireless network architecture and the ability to design AI, generative AI, and agentic AI solutions using technologies and approaches such as LLMs, RAG, knowledge graphs, vector databases, multi-agent systems, and AI orchestration frameworks.

The Senior Data Scientist will lead the creation of AI-powered engineering assistants, copilots, products, accelerators, and proof-of-concepts. The role also supports business growth by partnering with sales, solutioning, and leadership teams on bids, proposals, client presentations, executive briefings, workshops, and AI transformation roadmaps. Solutions will address operational needs such as incident triage, root cause analysis, predictive insights, anomaly detection, recommendations, and workflow orchestration.

The position brings together engineering knowledge, operational data, telemetry, documentation, and business processes into unified AI and data ecosystems. It also establishes architecture standards and governance for scalable, reliable, secure, observable, high-quality, and responsible AI. The role includes leading and mentoring multidisciplinary teams and influencing senior stakeholders to encourage enterprise AI adoption.

The posted location is Seattle, Washington. The base compensation range is $101,140 to $182,624. Capgemini states that its benefits package for regular, full-time employees may include paid time off, company-paid holidays, personal days, sick leave, medical, dental, and vision coverage, retirement savings plans, life and disability insurance, and employee assistance programs, subject to local policy and eligibility.

Requirements

• Deep understanding of wireless network architecture, including RAN, Core, Transport, OSS/BSS, Service Assurance, Network Operations, and Engineering workflows.
• Expertise designing AI, GenAI, and agentic AI solutions using LLMs, RAG, knowledge graphs, vector databases, multi-agent systems, and AI orchestration frameworks.
• Ability to conceptualize, prototype, and demonstrate AI products and accelerators.
• Experience supporting solutioning, bids, proposals, executive presentations, and client workshops.
• Experience building AI-powered solutions for incident management, root cause analysis, predictive maintenance, anomaly detection, and operational automation.
• Expertise in Azure, Databricks, Fabric, Snowflake, data engineering, MLOps, LLMOps, APIs, and cloud-native architectures.
• Experience creating enterprise knowledge repositories, semantic search capabilities, engineering copilots, and intelligent decision-support systems.
• Ability to define architecture blueprints, integration patterns, security standards, AI governance frameworks, and best practices.
• Proven ability to lead cross-functional teams, influence senior stakeholders, mentor engineers, and drive enterprise AI adoption.

Responsibilities

• Define and execute the AI strategy and architecture roadmap for network engineering, operations, automation, and digital transformation initiatives.
• Design and build AI-powered engineering assistants and copilots to improve knowledge discovery, troubleshooting, decision-making, and engineer productivity across network domains.
• Lead development of AI products, accelerators, and proof-of-concepts, rapidly prototyping solutions for business and operational challenges.
• Partner with sales, solutioning, and leadership teams on bids, proposals, client presentations, executive briefings, workshops, and AI transformation roadmaps.
• Develop intelligent operational solutions for incident triage, root cause analysis, predictive insights, automated recommendations, and workflow orchestration.
• Integrate structured and unstructured engineering knowledge, operational data, telemetry, documentation, and business processes into unified AI and data ecosystems.
• Establish AI architecture standards and governance for scalability, reliability, security, observability, data quality, and responsible AI compliance.
• Lead and mentor multidisciplinary teams of AI engineers, data scientists, platform engineers, and domain experts.
• Drive continuous innovation and adoption of emerging AI technologies.

Benefits

• Paid time off, including vacation of 12–25 days depending on employee grade, company-paid holidays, personal days, and sick leave, based on policy.
• Medical coverage.
• Dental coverage.
• Vision coverage.
• Retirement savings plans, such as a 401(k) in the U.S.
• Life insurance.
• Disability insurance.
• Employee assistance programs.
• Other benefits as provided by local policy and eligibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed