Data Scientist
Permanent @DHL posted 4 days ago in Information Technology (ICT) Shortlist Email JobJob Detail
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Job ID 5724
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Work Model: In-Office / On-Site
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Experience Level: 2 Years
Job Description
Role Outline
To design, build, and operationalize machine learning and optimization solutions that deliver measurable improvements in planning, execution, and service performance across warehousing and logistics. Translate high-value use cases into production-ready models with clear ROI and strong user adoption.
Key Tasks
• Frame analytical problems, define success metrics, and design robust experiments (A/B tests or quasi experimental designs).
• Build data pipelines and validated training/evaluation datasets and establish and maintain feature stores as needed.
• Train, evaluate, and iterate on models (including tree based methods, time series, clustering, and deep learning when appropriate).
• Implement Machine Learning Operations practices, including experiment tracking, model registry, CI/CD, and monitoring for drift and performance degradation; automate retraining where feasible.
• Collaborate with Data Engineering to deliver reliable batch and API integrations into BI platforms and operational systems.
• Ensure Responsible AI practices: privacy by design (POPIA), bias and impact assessments, and comprehensive model documentation (e.g., model cards).
• Communicate insights clearly through data storytelling and support stakeholders via dashboards and intuitive UX integrations (e.g., Power BI).
• Comply with Information Security and POPIA requirements; enforce privacy by design throughout the machine learning lifecycle.
• Maintain model cards, data lineage, validation reports, and change logs to ensure audit readiness.
Measurement Criteria / KPIs
• Deliver at least one complex, one medium, and two simple projects per cycle with successful implementation outcomes.
• Achieve measurable improvements in targeted KPIs for each implemented solution.
• Realize cost reductions for each completed project, aligned with business case expectations.
• Maintain time to production of ≤ 12 weeks for priority models, with ≥ 80% adoption by intended users.
• Ensure model reliability of ≥ 99% uptime, with documented drift detection processes and defined retraining SLAs.
Qualifications & Experience
Education:
• Bachelor’s degree or equivalent experience (Statistics, Computer Science, Engineering, or related).
• Azure Machine Learning, Databricks, Machine Learning Operations; CI/CD with Azure DevOps (ADO) or GitHub; testing (pytest).
• Strong Python skills (pandas, NumPy, scikit-learn), SQL; experience at scale with time-series and tabular Machine Learning.
Experience:
• Minimum 2 years in applied data science; 3–7+ years preferred.
• Optimization (OR-Tools/Pyomo); forecasting frameworks; SHAP/explainability.
• Experience embedding model outputs into WMS/TMS/ERP workflows and Power BI.
• Data cleansing and processing; databases/data warehousing and integration; cloud computing (Azure preferred).
• Predictive modelling and machine learning; statistics and mathematics; workflow automation.
• Business decision-making, stakeholder management, consulting, change management, presentation and storytelling.
• Data visualization (Power BI); data protection and privacy regulations; technology trends; project management.
Functional Competencies
• Stakeholder management.
• Identifying and analysing information to understand project requirements, key data, and decision drivers.
• Applying technical skills to create and model scenarios for current and future operational solutions.
• Developing value based solutions with a focus on operational improvement.
• Delivering accurate and competitive resource and cost models.
• Ensuring the quality and rigour of processes, documentation, and risk assessments.
• Demonstrating effective questioning and facilitation skills with clear and accurate communication.
• Developing and presenting compelling value based solutions.
• Aligning work with the strategic objectives of the BU / Cluster / Region.
• Providing high quality, professional contributions to documented solutions.
• Building and leveraging internal and external networks for collaboration and learning.
• Maintaining awareness of supply chain trends, suppliers, and competitor activity.
• Plans and manages own work and supports key project stakeholders through to handover.
DPDHL Core Competencies & Skills
• Maintains effective relationships with customers.
• Develops and delivers high quality / innovative products, services, or solutions.
• Focuses on customer needs and gains their commitment.
• Gains management / colleague support to meet customer needs.
• Ensures strategies / plans are aligned and reflect others’ views.
• Develops strategies / plans aligned to broader organizational strategy.
• Communicates strategy.
• Establishes clear, challenging, and achievable objectives.
• Aligns resources and the organization within own area of responsibility to achieve objectives.
• Regularly reviews and communicates progress against objectives and adjusts as needed.
• Champions continuous improvement and innovation.
• Inspires results and respect by empowerment, accountability recognition and rewards recognizing the contribution of others.
• Provides employees, colleagues, and business partners with candid and regular feedback.
• Provides employees with development opportunities.
• Supports employees with career opportunities.
• Inspires others to develop themselves.
• Conveys a clear sense of personal goals and values.
• Actively seeks feedback to improve performance.
• Develops new skills and modifies behaviours based on feedback.
• Takes personal responsibility for career and development.
Languages
English – verbal and written.
Required Skills
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