Data Scientist Procurement

As a Data Scientist embedded in the Procurement department, you will be a key enabler of data-driven transformation. You will leverage advanced analytics, machine learning, and automation to optimize procurement strategies, enhance supplier performance, and drive cost efficiencies. This role requires a blend of technical expertise, business acumen, and strong communication skills to influence decision-making at all levels.

Key Responsibilities

Data Modeling & Predictive Analytics

Build and maintain statistical and machine learning models to forecast procurement trends, supplier performance, and cost-saving opportunities.

• Develop lead time prediction models and risk scoring algorithms for supplier evaluation.
• Apply regression, classification, clustering, and time-series forecasting techniques to procurement datasets.
• Spend & Cost Analytics

Analyze procurement spend across categories, suppliers, and geographies to identify inefficiencies, maverick spend, and opportunities for consolidation or renegotiation.

• Create dashboards and KPIs to monitor procurement performance and savings realization.
• Supplier Intelligence & Risk Management
• Design supplier scoring systems based on performance, compliance, ESG metrics, and risk exposure.
• Integrate third-party data sources (e.g., financial ratings, geopolitical risk) to enrich supplier profiles.
• Automation & Data Engineering

Automate data pipelines and reporting workflows using Python, SQL, and tools like Qlik, Power BI, or Tableau.

Collaborate with IT and data engineering teams to ensure data quality, governance, and integration with ERP and procurement platforms (e.g., SAP, Salesforce).

Strategic Collaboration

Partner with procurement managers and category leads to support strategic sourcing, supplier onboarding, catalog optimization, and contract lifecycle management.

Translate complex data insights into actionable recommendations for stakeholders.

Innovation & Continuous Improvement

Lead or contribute to innovation sprints, mind map sessions, and simplification initiatives to enhance procurement agility.

Stay current with emerging technologies in AI, NLP, and procurement analytics.

Proven experience in data science, ideally within supply chain, procurement, or operations analytics.

Proficiency in Python, SQL, and data visualization tools (e.g., Power BI, Qlik, Tableau).

Experience with cloud platforms (e.g., AWS, Azure, GCP) and data pipeline tools (e.g., Airflow, dbt) is a plus.

Familiarity with procurement systems (e.g., Netsuite, Coupa, Salesforce).

Strong analytical and problem-solving skills with the ability to communicate insights clearly to non-technical stakeholders.

Ability to manage multiple projects and prioritize in a fast-paced environment.