Data Scientist

We’re looking for a hands-on data scientist with a passion for procurement innovation, someone who combines technical depth with business awareness, and can bring AI/ML capabilities to life in a scalable and impactful way.

Key Responsibilities

Model Maintenance and Expansion: Maintain and enhance existing Vertex AI models in our data lake (e.g., for classification, enrichment, and clustering).

New ML model development: Design and deploy new machine learning models for procurement use cases (i.e. spend analytics and allocating to the relevant category, savings opportunity prediction, etc.)

Data Enrichment: Engineer procurement-specific features from structured and semi-structured data sources.

ML/AI Pipeline Ownership: Own the full ML lifecycle — from experimentation to production — in collaboration with data engineering. Leverage tools like Vertex AI, BigQuery, DBT, and Python-based pipelines to ensure automation, reproducibility, and scalability.

Innovation & Continuous Improvement: Stay ahead of the curve by researching the latest trends in AI/ML, including generative AI and foundation models, and evaluating their applicability in procurement.

Data Products: Co-create intelligent, ML-powered data products with procurement stakeholders. These products support both internal operations and client-facing services — including anomaly detection dashboards, forecasting tools, and what-if scenario simulators — all powered by ML, external data, and business context.

Skills & Requirements

• Bachelor's degree in data science, statistics, computer science or a related field. Advanced degree in any of these fields is also desired.
• Experience with cloud-based data platforms (GCP).
• Hands-on proficiency with Python, SQL, and ML frameworks.
• Experience with Vertex AI, BigQuery, and data transformation tools (e.g., DBT).
• Familiarity with classification, clustering, forecasting, and NLP models relevant to procurement
• Excellent communication skills with the capability to translate intricate data findings into actionable insights for non-technical stakeholders.