TL;DR

Data Scientist (Data & ML Engineering): Building and managing data and ML engineering projects with an accent on data pipeline development and visualization. Focus on collaborating with cross-functional teams to deliver actionable insights and promote data literacy.

Location: Singapore

Company

Leading provider of globally integrated and port-centric supply chain, transportation, and logistics solutions.

What you will do

Build and manage Data & ML Engineering projects.
Develop and maintain data/ML pipelines using Snowflake and Azure.
Create and implement data visualizations using Qlik.
Ensure seamless integration and deployment of models through DevOps and ML ops processes.
Collaborate with cross-functional teams to understand data needs and deliver actionable insights.
Advocate for data-driven decision-making across the organization.

Requirements

Minimum of 3+ years of end-to-end implementation experience in data warehouse and data management projects.
Extensive hands-on experience architecting and delivering solutions on the Azure Data platform, Snowflake, SnowPark, ML Ops and DevOps.
Logistics and Transportation domain experience is preferred.
Agile/DAMA/Azure certification is a plus.
Strong communications skills.