End-to-End Data Scientist: Azure ML & Business Impact

Scan Global Logistics; Muntinlupa; On-site; PHP 900,000 - 1,300,000; Full time

Job summary

Scan Global Logistics seeks a data scientist to translate business questions into deployed AI solutions across logistics operations, finance, and commercial domains. You will frame problems, build and validate models in Azure Machine Learning and Microsoft Fabric, and present results to non-technical stakeholders.

You will engineer data pipelines using Python and SQL, deploy with MLflow, monitor performance and drift, and collaborate with AI teams on LLM strategies while upholding data

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

Python

SQL

Azure Machine Learning

Microsoft Fabric

MLflow

Power BI

Data storytelling

Education

Data science / statistics / CS / math degree

Tools

Azure Machine Learning

MLflow

Microsoft Fabric

Power BI

Job description

Scan Global Logistics seeks a data scientist to translate business questions into deployed AI solutions across logistics operations, finance, and commercial domains. You will frame problems, build and validate models in Azure Machine Learning and Microsoft Fabric, and present results to non-technical stakeholders.

You will engineer data pipelines using Python and SQL, deploy with MLflow, monitor performance and drift, and collaborate with AI teams on LLM strategies while upholding data