As the data science expert on the team, you will own the full lifecycle of data science work—from problem framing and modeling to production deployment. This is not a pure research or pure analysis role. We are looking for a “full-stack” data scientist who can both rapidly prototype using cutting-edge AI tools and engineer models into real, production-ready systems. You’ll partner closely with business teams to turn data capabilities into measurable commercial value.
- Independently drive the end-to-end lifecycle of data science projects: business problem decomposition, data exploration, feature engineering, modeling, evaluation, deployment, and monitoring.
- Leverage AI-assisted coding tools (e.g., Cursor, GitHub Copilot, Claude Code) to dramatically accelerate development and quickly turn ideas into working prototypes and products.
- Engineer experimental models into stable, maintainable, and scalable production-grade services, owning their live performance.
- Build and maintain data pipelines and ML workflows, ensuring data quality and reproducibility.
- Collaborate across business, product, and engineering teams to take projects from 0 to 1 independently.
1. AI Vibe Coding Capability
- Proficient in using AI-assisted coding tools for rapid development; able to effectively drive AI through natural language to code, debug, and refactor.
- Strong “human-AI collaboration” working style: knows how to break down tasks, write high-quality prompts, and review and control the quality of AI-generated code.
- Hands-on experience rapidly building end-to-end proofs of concept (POCs) with AI tools.
2. Data Science Engineering Capability
- Solid software engineering foundation: familiar with version control (Git), coding standards, unit testing, and CI/CD practices.
- Able to independently deploy models to production; experienced with containerization (Docker), API services, and model monitoring.
- Familiar with the data engineering stack (e.g., SQL, Spark, Airflow, or equivalent) and able to build reliable data pipelines.
- Strong command of Python, with the ability to write clean, maintainable, production-grade code.
3. General Requirements
- Degree in Computer Science, Statistics, Mathematics, or a related field; 5+ years of relevant data science experience.
- Strong foundation in machine learning and statistical modeling.
- Strong business acumen and communication skills; able to translate technical outcomes into business language.
- Self-driven, independent, and able to deliver high-quality results with limited resources.
- Experience in retail, beauty, or e-commerce.
- Familiarity with LLM application development or practices such as RAG and AI agents.
- Community, in which authenticity is embraced, and the strength of our differences fuels our collective spirit.
- Culture of empowerment, learning & growth, that offers you the tools, space and opportunity to learn, innovate and lead.
Work that brings fulfillment. From delighting clients every day, to inspiring our industry at large, every action makes a difference.
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Join us and belong to something beautiful.
