Data Scientist

General Overview of the Job:

A data scientist who works on the Microsoft data platform and is measured on decisions changed, not models trained. The role covers the full path from framing a business question to a deployed, monitored model, and includes presenting results to non-technical stakeholders in logistics operations, finance and commercial.

Job Duties and 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.

Qualifications and Certifications: 

  • 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.
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Deadline:
Contact person:
Jose Manuel Catindig HR Associate
Office: Manila, Alabang (SSC), Philippines
Location: Alabang–Zapote Road, 1780, Muntinlupa, Philippines

Scan Global Logistics is a Global full-service logistics provider headquartered in the Nordic, who excel in uncomplicating logistics through tailored solutions made by skilled specialists, proud problem-solvers and passionate entrepreneurs.
Since 1975, the core of our DNA has been a ‘can-do-attitude’, agility and the willingness to always go the extra mile and we are not afraid to go left when others go right. For us, every challenge is an opportunity. We go above and beyond to bring anything to anywhere – whether by road, rail, ocean, air or any other modes of transportation.