As a Data Analyst in the Land Transportation Unit of our Supply Chain Department, you will play a crucial role in optimizing the efficiency and effectiveness of our land transportation operations.
You will be responsible for collecting, analyzing, and interpreting data related to transportation routes, vehicle performance, fuel consumption, driver behavior, and other key metrics.
Your insights will drive decision-making processes, enabling us to streamline our transportation processes, reduce costs, improve delivery times, and enhance overall customer satisfaction. Additionally, you will collaborate with cross-functional teams to develop predictive models, generate actionable reports, and identify opportunities for process improvements.
This role requires strong analytical skills, proficiency in data visualization tools, and a deep understanding of transportation logistics. If you are passionate about leveraging data to drive operational excellence and eager to make a meaningful impact in the supply chain industry, we encourage you to apply.
Additionally, you’ll play a crucial role in implementing technology solutions, such as ERP systems, to streamline operations and ensure compliance with industry regulations.
Strong analytical skills, industry knowledge, and effective communication are essential for success in this role.
Responsibilities
Tool and Application Development:
Design, develop, and maintain tools and applications tailored for tracking relevant indices and Key Performance Indicators (KPIs) specific to land transportation.
Collaborate with stakeholders to understand requirements and translate them into functional specifications for tool development.
Utilize programming languages and software tools such as Python, R, SQL, and Tableau to create user-friendly dashboards and reporting interfaces.
Implement automation where possible to streamline data collection, processing, and visualization processes.
Data Analysis:
Conduct in-depth analyses of transportation data to identify trends, patterns, and outliers.
Utilize statistical techniques and predictive modeling to forecast transportation demand, optimize routes, and improve operational efficiency.
Perform root cause analysis to identify factors impacting transportation performance and propose data-driven solutions for improvement.
Collaborate with cross-functional teams to gather relevant data inputs and ensure data integrity throughout the analysis process.
Management Reporting:
Generate regular reports and ad-hoc analyses for management review, providing insights into transportation performance, cost trends, and operational metrics.
Present findings and recommendations to key stakeholders, including transportation managers, supply chain directors, and executives, in a clear and concise manner.
Customize reporting formats and metrics based on the needs of different stakeholders, ensuring alignment with strategic objectives and business priorities.
Continuously refine reporting processes and formats based on feedback and changing business requirements to enhance the effectiveness of decision-making.
Data Quality Assurance:
Establish data quality standards and protocols to ensure the accuracy, completeness, and consistency of transportation data sources.
Conduct regular audits and validations of data inputs to identify discrepancies or anomalies and implement corrective actions as needed.
Collaborate with IT teams to optimize data infrastructure and systems for data collection, storage, and retrieval, ensuring data accessibility and reliability for analysis purposes.
By fulfilling these primary job functions, the data analyst in the land transportation unit plays a crucial role in optimizing transportation operations, driving cost savings, and improving overall supply chain performance.
Requirements
Bachelor’s degree in Data Science, Statistics, Computer Science, Engineering, or a related field with a minimum of 2nd class upper or its equivalent. A master’s degree or a professional qualification will be an added advantage.
Maximum of 2 years of post-graduation experience.
Proficiency in programming languages such as Python, R, or SQL, with the ability to manipulate and analyze complex datasets efficiently.
Experience with data visualization tools like Tableau, Power BI, or Matplotlib to create insightful visual representations of data for stakeholders.
Understanding of statistical methods and concepts, including hypothesis testing, regression analysis, and predictive modelling
Preferred Qualifications/ Experience
Strong analytical abilities with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
Excellent communication skills, both written and verbal, to effectively convey insights and findings to diverse stakeholders, including technical and non-technical audiences.
Ability to work collaboratively in a team environment, contribute ideas, and support team goals while also being capable of working independently on assigned tasks.
Excellent communication skills, both written and verbal, to effectively convey insights and findings to diverse stakeholders, including technical and non-technical audiences.
Strong problem-solving skills with the ability to identify issues, propose solutions, and implement strategies to improve data quality and analysis processes.
Willingness to learn and adapt to new technologies, tools, and methodologies in the field of data analysis and transportation analytics.
Demonstrated the ability to manage multiple tasks and prioritize effectively to meet deadlines in a fast-paced environment.