Lead Gen AI for Network Services | Data Scientist

SoftServe

United States

Hybrid

USD 140,000 - 220,000

Full time

2 days ago
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Benefits offered by this job

Flexible Work Model
Work from home / hybrid
Health coverage
Paid time off
Wellness support
Learning opportunities
Advanced Tech Communities

Job summary

SoftServe is seeking a Data Scientist Lead - Gen AI for Network Services to drive responsible AI adoption across the organization. You will identify AI opportunities, prioritize initiatives, and coordinate delivery with infrastructure and central AI teams to realize measurable business outcomes.

The role requires experience delivering AI-enabled solutions, governance, and change leadership. You will work in a large, matrixed environment, enabling adoption of enterprise AI platforms and reusable

Qualifications

  • Experience delivering AI-enabled transformations at scale.
  • Ability to define KPIs and measure value realization.
  • Experience in enterprise change leadership.

Responsibilities

  • Lead AI demand intake and prioritization across Network Services.
  • Assess AI use cases based on business value, feasibility, data readiness, and risk.
  • Coordinate delivery of AI capabilities across business, technology, and central AI teams.
  • Ensure AI governance, compliance, and risk processes are followed.
  • Track success metrics, adoption, value, risks, and delivery progress.

Skills

AI transformation
Product delivery
Stakeholder management
Governance & risk

Tools

LLMs
MLOps
Data architecture

Job description

SoftServe is seeking a Data Scientist Lead - Gen AI for Network Services to drive responsible AI adoption across the organization. You will identify AI opportunities, prioritize initiatives, and coordinate delivery with infrastructure and central AI teams to realize measurable business outcomes.

The role requires experience delivering AI-enabled solutions, governance, and change leadership. You will work in a large, matrixed environment, enabling adoption of enterprise AI platforms and reusable

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