Regional Data Analyst/ Scientist (Logistics)

Key Responsibilities:

• Develop and implement analytical, predictive, and machine learning models that generate meaningful insights to drive business growth, improve operational performance, optimize resource allocation, and mitigate risks.
• Explore multiple structured and unstructured data sources and perform exploratory data analysis (EDA) to uncover patterns, trends, and actionable business opportunities.
• Design, engineer, and evaluate valuable data features that enhance analytics, forecasting accuracy, and machine learning model performance.
• Apply statistical techniques, predictive analytics, and machine learning algorithms to solve complex business problems and support strategic decision-making.
• Partner with business stakeholders to identify opportunities, recommend data-driven actions, and evaluate performance improvement initiatives through data experimentation and quantitative analysis.
• Build and enhance advanced analytics capabilities aligned with strategic business use cases and operational objectives.
• Develop forecasting, segmentation, optimization, and anomaly detection models to support business planning and operational efficiency.
• Develop, maintain, and optimize interactive dashboards, reports, and visualizations using Microsoft Fabric and Power BI.
• Communicate analytical findings through clear storytelling and effective data visualization techniques, translating complex technical insights into business-friendly recommendations.
• Provide technical and functional support to internal users on BI tools, reporting platforms, analytics solutions, and data science use cases.
• Collaborate closely with Data Engineering and Data Governance teams to ensure alignment on project timelines, requirements, data quality, feature availability, and platform enhancements.
• Support the deployment, monitoring, and continuous improvement of analytical and machine learning models in production environments.
• Monitor emerging trends and advancements in AI, machine learning, Microsoft Fabric, Azure AI, Power BI, and analytics technologies, recommending improvements and best practices where appropriate.
• Support the adoption of data-driven decision-making and AI-enabled business processes across the organization.
• Ensure proper documentation of analytical methodologies, model assumptions, reporting logic, and business intelligence solutions.

Candidate Profile:

• Bachelor's degree in Data Science, Business Analytics, Mathematics, Statistics, Computer Science, Information Engineering, or a related discipline. Master's degree is an advantage.
• 5+ years of experience in Data Analytics, Data Science, Business Intelligence, Reporting, or related analytical roles.
• Strong understanding of business operations, data requirements, performance metrics, and commercial decision-making processes.
• Hands-on experience in statistical analysis, predictive modelling, machine learning, forecasting, segmentation, optimization, and model evaluation techniques.
• Experience applying supervised and unsupervised learning algorithms to solve real-world business challenges.
• Proficient in SQL and Python and/or R for data extraction, transformation, analysis, modelling, and reporting.
• Experience with machine learning libraries and frameworks such as Scikit-learn, XGBoost, TensorFlow, PyTorch, or similar technologies is preferred.
• Hands-on experience developing and managing Power BI dashboards, reports, and visualizations.
• Strong communication, presentation, storytelling, and stakeholder management skills.
• Experience with Microsoft Fabric, Azure Databricks, Azure Machine Learning, or related cloud analytics platforms is highly desirable.
• Familiarity with MLOps concepts, model deployment, and model monitoring practices is an advantage.
• Experience in logistics, supply chain, transportation, or related industries is highly preferred.

About the Organization:

A leading global logistics and supply chain solutions provider with a strong international presence. The organization continues to invest in digital transformation, cloud technologies, and advanced analytics capabilities to drive operational excellence and business innovation.

Operating within a complex and fast-paced environment, the company places significant focus on leveraging modern data platforms and cloud technologies to support business growth, improve decision-making, and enhance customer experience.

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