Sr Data Scientist/PERM/Retail/35-48K HKD P/M

Role Overview

Our client, a leading global retail and consumer enterprise, is looking for a highly analytical and impact-driven Senior Data Scientist to join their centralized Advanced Analytics & AI team. This is a critical role for a practitioner who excels at solving complex, real-world commercial challenges through a combination of predictive data modeling and modern AI innovation to directly support high-impact storefront and operational use cases.

A Typical Day in This Role

• Statistical & Predictive Modeling: Design, develop, and refine predictive models and machine learning algorithms using an evidence-based approach to optimize storefront operations, inventory exposure, and commercial layouts.

• A/B Testing & Experimentation: Architect and execute robust A/B testing frameworks and "Control vs. Test" operational matching methodologies to measure the real-world impact of commercial modifications and layout changes.

• Modern AI Integration: Implement Large Language Models (LLMs) and NLP techniques to automate processes, handle unstructured text/product data, and inject data-driven logic into live operational applications.

• Business Insights: Translate complex predictive outputs and experimental results into clear, actionable business insights, communicating strategies effectively across both digital and physical retail channels.

Success Will Depend On:

• Experience & Background: 3 to 5 years of professional experience in Data Science with a deep, fundamental background in Statistics, Mathematics, or a highly quantitative field.

• Commercial Acumen: Strong business sense within the consumer goods, retail, or fast-moving corporate sectors, with a proven ability to leverage data modeling to solve storefront and operational challenges.

• Technical Proficiency:

  • Solid knowledge of predictive modeling, multivariate statistical techniques, hypothesis testing, and experimental design (A/B testing).

  • Proficiency in Python and SQL, with experience utilizing major cloud platforms (e.g., Databricks, Azure, or GCP).

  • Hands-on experience building or applying models with NLP and LLMs.