Senior Data Analyst, Solutions at DSV

Tertiary Qualification(s)

•  Bachelor’s or master’s degree in an analytical discipline such as Data Science, Mathematics, Statistics, Computer Science, Industrial Engineering, or a related field. (Honors degree preferable)

Additional Computer Skills

• SQL (MS SQL, PostgreSQL, MySQL): Ability to write and optimize complex queries for efficient data extraction, transformation, and analysis.
• Power BI & Data Visualization: Advanced Power BI development, including DAX, Power Query, custom visuals, and automated report generation.
• Python (R is a plus): Proficiency in Python for data manipulation (Pandas, NumPy), machine learning (Scikit-learn, TensorFlow), and automation.

Job-related Requirements

Experience:

• +5 years of experience in a data analytics, data science, or business intelligence role within a supply chain
• Experience working with large datasets from multiple sources (ERP, WMS, TMS, FMS) to drive operational insights and efficiencies.
• Hands-on experience in forecasting, optimization, and predictive modelling to support supply chain decision-making.

Soft Skills:

• Effective Communication: Strong written and verbal communication skills to present complex data findings in a clear, concise, and actionable manner.
• Attention to Detail & Accuracy: Well-organized with a strong focus onprecision, ensuring high data quality and reliability.
• Results-Driven Mindset: Demonstrates dependability, persistence, productivity, and resourcefulness to achieve business goals.
• Innovative & Forward-Thinking: Passion for innovation, embracing change, questioning the status quo, and seeking new approaches to problem-solving.
• Time Management & Prioritization: Ability to manage multiple projects efficiently, meeting deadlines while maintaining data integrity.
• Analytical & Logical Thinking: Strong problem-solving abilities, with a structured and logical approach to identifying trends, inefficiencies, and business opportunities.

Technical Skills:

• Business Requirements Analysis: Ability to interpret business needs and translate them into data-driven solutions and specifications.
• Data Engineering & ETL: Understanding of data pipelines, ETL processes, and integration of multiple data sources.
• Warehouse & Transport Systems Knowledge: Familiarity with Warehouse Management Systems (WMS), Transportation Management Systems (TMS), and Freight Management Systems (FMS) to extract and analyse operational data

ADDED ADVANTAGES FOR THIS ROL

• +5 years of experience in a data analytics, data science, or business intelligence role within a Retail
• Strong foundational knowledge of Supply Chain Management— certification (e.g., APICS CSCP, CPIM, SCOR-P) or proven industry experience is highly advantageous.
• Big Data & Cloud Platforms (Advantageous): Experience with Azure Synapse, AWS Redshift, Google BigQuery, or Snowflake

MAIN PURPOSE OF THE ROLE

• The Senior Data Scientist / Analyst will report into the Senior Manager, Planning & Transport Operations based in Johannesburg.
• This role be part of the Solutions FMS Team who are responsible for inventory optimization, warehouse and transport planning, execution and transport management for the South African Solutions Business and Clients.
• The core purpose of the role is to establish engagement opportunities with customers and operations, interpret large volumes of data from various sources and translating the intelligence into meaningful information which when applied will improve service to Clients, and increase operational productivity.
• The ability, meaning market related know how and experience on accessing, and querying large data sets on various industry standard systems, building models to process and interpret the data, analysis, discovery of useful information, detection of patterns patterns, anomalies, trends and behaviors, forecast future demand, incorporate client business intelligence, identify

DUTIES & RESPONSIBILITIES

• Data Analysis & Insights: Analyze, interpret, and model structured and unstructured data from multiple supply chain systems (e.g., WMS, TMS, ERP) to uncover trends, inefficiencies, and opportunities for cost savings and process optimization.
• Predictive & Prescriptive Analytics: Develop and implement machine learning models and statistical techniques to forecast client demand, optimize inventory levels, and enhance operational planning for inbound and outbound logistics.
• Advanced Data Visualization & Reporting: Design and maintain interactive dashboards and reports using Power BI and other analytics tools, ensuring real-time visibility into key performance metrics across supply chain operations.
• Operational Efficiency & Process Improvement: Identify bottlenecks and inefficiencies in transportation, warehousing, and inventory management by leveraging data-driven insights, and propose data-backed solutions to improve overall performance.
• Data Governance & Quality Management: Validate, clean, and stand