Senior AI Data Scientist: GenAI, Agent Workflows (Hybrid)

Nestlé IT & Digital Americas; Arlington (VA); Hybrid; USD 140,000 - 196,000; Full time

Benefits offered by this job

401k with company match

Healthcare coverage

Incentives / performance-based bonuses

Job summary

Nestlé IT & Digital Americas seeks an Expert AI Data Scientist to frame ambiguous business problems and own AI solutions end-to-end, blending product management and engineering. You will guide AI agent workflows, build scalable scaffolding, and drive durable adoption across Nestlé USA.

The role emphasizes collaboration with cross-functional teams, expertise in Python, and hands-on ML with enterprise-scale platforms such as Databricks and Snowflake.

Qualifications

• Bachelor's degree required in a technical field.
• 7+ years partnering with stakeholders to translate business needs into technical solutions.
• 5+ years building and shipping AI/ML solutions with real user adoption.
• 3+ years deploying enterprise-scale solutions including MLOps and cloud platforms.

Responsibilities

• Lead end-to-end AI applications from concept to adoption.
• Design evaluation frameworks and monitoring for AI outputs.
• Orchestrate AI agents across parallel work streams and reusable workflows.
• Collaborate with global IT & Digital teams to scale AI solutions.
• Document decisions, learnings, and incidents to improve processes.

Skills

Python programming

AI/ML solutions

Cross-functional collaboration

AI agent patterns

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Data Science, or a related field

Master's or PhD preferred

Tools

Databricks

Snowflake

LLM concepts

Job description

Nestlé IT & Digital Americas seeks an Expert AI Data Scientist to frame ambiguous business problems and own AI solutions end-to-end, blending product management and engineering. You will guide AI agent workflows, build scalable scaffolding, and drive durable adoption across Nestlé USA.

The role emphasizes collaboration with cross-functional teams, expertise in Python, and hands-on ML with enterprise-scale platforms such as Databricks and Snowflake.