Data Scientist, Senior-Level

Role overview

Accountabilities

• Design and orchestrate agentic AI workflows, generative AI applications, LLM solutions, and autonomous systems.
• Translate business needs into backlogs, user stories, technical requirements, and execution roadmaps.
• Own Data and AI initiatives from strategy through architecture, development, implementation, and delivery.
• Design modular, scalable, reusable Data and AI components for enterprise environments.
• Apply data quality, lifecycle, privacy, governance, security, and production-readiness practices.
• Collaborate across business, engineering, data, project management, and other technical teams.
• Lead demonstrations, architecture discussions, workshops, and stakeholder engagements.
• Improve enterprise data ecosystems and accelerate advanced AI adoption.
• Provide technical leadership and connect technical solutions to strategic business outcomes.

Requirements

• At least 5 years of professional experience in data science, machine learning, AI architecture, or a related field.
• Strong foundations in statistics, mathematics, machine learning, and cloud-native data platforms.
• Experience designing, building, or orchestrating agentic AI, generative AI, LLM, or autonomous workflow solutions.
• Ability to translate business requirements into product backlogs, user stories, priorities, and roadmaps.
• Deep understanding of data quality, lifecycle management, privacy, governance, and data stewardship.
• Ability to architect modular, scalable, reusable Data and AI components.
• Technical leadership and client-facing advisory experience are required.
• Excellent analytical, problem-solving, communication, and collaboration skills are required.
• Fluent English at B2 level or higher is required.
• Ability to work independently and own complex multidisciplinary initiatives.

Work arrangement

• The benefits section states that the role offers a remote work opportunity.

Benefits

• Contribute to large-scale Data and AI transformation initiatives.
• Work with generative AI, agentic systems, LLM applications, cloud-native data platforms, and modern AI architectures.
• Influence architecture, product direction, and strategic technology decisions.
• Collaborate with diverse stakeholders across global enterprise environments.
• Expand expertise across data science, AI architecture, product ownership, governance, and transformation.