You will apply rigorous analytical thinking and modern AI capabilities to design, build, and scale high-impact solutions.
Design, develop, and deploy GenAI-powered internal applications, copilots, and workflow accelerators.
Build reusable AI components, including retrieval pipelines, structured prompting patterns, orchestration workflows, and evaluation harnesses.
Develop and maintain statistical and machine learning models to support automation, optimization, forecasting, and classification use cases.
Design retrieval strategies that connect LLMs to trusted internal knowledge sources, ensuring grounded and reliable outputs.
Implement evaluation and validation frameworks to measure quality, accuracy, and consistency of AI-driven systems.
Partner cross-functionally to identify high-value opportunities for AI enablement across the organization.
Create reusable datasets, feature pipelines, and experimentation frameworks to support iterative development.
Document methodologies, assumptions, and implementation details to ensure transparency and reproducibility.
Uphold high standards for quality, reliability, and responsible AI practices.
Contribute to peer review processes to ensure technical rigor and maintainability.

5+ years of relevant experience in Data Science, Machine Learning, or AI-focused roles.
Demonstrated experience applying machine learning techniques in production or enterprise environments.
Hands-on experience building applications or workflows powered by large language models (LLMs).
Evidence of a builder mindset through shipped AI tools, internal platforms, or automation solutions.
Strong curiosity for emerging AI technologies and the ability to evaluate and adopt them responsibly.
Academic background in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, Economics, or a related field.

Senior Data Scientist

Key skills