Data Scientist: Build & Deploy ML for Business Impact

Scan Global Logistics; Muntinlupa; On-site; PHP 1,200,000 - 1,900,000; Full time

Job summary

Scan Global Logistics seeks a data scientist to work on the Microsoft data platform, driving decisions through deployed analytics rather than just models. The role spans framing a business question to deploying, monitoring, and presenting results to logistics, finance and commercial stakeholders.

You will frame questions with stakeholders, build and deploy models in Azure ML and Fabric, engineer data pipelines, productionize with MLflow, monitor drift and data quality, and share actionable

Qualifications

• Master's or Bachelor's degree in data science, statistics, computer science, mathematics or another quantitative field.
• Microsoft Certified: Azure Data Scientist Associate; Fabric Analytics Engineer Associate or Azure AI Engineer Associate is an advantage.
• At least three years of applying machine learning and statistical methods to business problems.

Responsibilities

• Frame business questions with stakeholders, then build, validate and deploy models in Azure Machine Learning and Microsoft Fabric.
• Engineer features and data pipelines over lakehouse and warehouse data using Python and SQL.
• Put models into production with MLflow and managed endpoints, and monitor them for drift, data quality and performance.
• Communicate findings through Power BI and written analysis, so that the recommendation is clear to a non-technical audience.
• Partner with the AI team on evaluating large language model solutions and apply data governance and privacy requirements to every dataset used.

Skills

Stakeholder communication

ML deployment

Framing business questions

Feature engineering

Model monitoring

Power BI reporting

LLM evaluation

Education

Master's or Bachelor's in data science / statistics / CS / maths

Tools

Azure Machine Learning

Microsoft Fabric

MLflow

Power BI

Python

SQL

Job description

Scan Global Logistics seeks a data scientist to work on the Microsoft data platform, driving decisions through deployed analytics rather than just models. The role spans framing a business question to deploying, monitoring, and presenting results to logistics, finance and commercial stakeholders.

You will frame questions with stakeholders, build and deploy models in Azure ML and Fabric, engineer data pipelines, productionize with MLflow, monitor drift and data quality, and share actionable