Data Scientist

Role & responsibilities

Collect, process, and analyze large datasets from multiple logistics verticals (freight, warehousing, customs, fleet operations, etc.).

Develop and deploy predictive and prescriptive models to optimize routing, demand forecasting, pricing, and warehouse utilization.

Build machine learning algorithms for trend detection, anomaly detection, and automation of logistics workflows.

Create real-time dashboards and data visualizations to support strategic business decisions. Partner with Product, Operations, and Business teams to identify analytics opportunities and design data solutions

Conduct deep-dive analyses to understand business performance, inefficiencies, and improvement areas.

Maintain high standards of data accuracy, integrity, and compliance with internal data policies. Document analytical methodologies, models, and outcomes for future reference and scalability.

Preferred candidate profile

Strong understanding of data analytics, machine learning, and statistical modeling techniques. Proficiency in Python, SQL, and data visualization tools (Power BI, Tableau, or equivalent). Experience with data wrangling, ETL pipelines, and working on large, unstructured datasets. Solid grasp of predictive analytics, time-series forecasting, and optimization models.

Experience with logistics, supply chain, or operations data preferred.

Excellent problem-solving and critical-thinking abilities.

Strong communication skills to present complex insights to non-technical stakeholders.

Qualification Required

Bachelors or masters degree in data science, Computer Science, Statistics, Mathematics, or a related field.

Certification in Machine Learning, Data Analytics, or AI will be an added advantage.