Sr. Analyst, Global Data Science Supply Chain

Colgate

3d•Remote

About The Position

The Global Data Science & Advanced Analytics (GDS&AA) vertical at Colgate-Palmolive focuses on solving high-impact business problems with measurable financial outcomes. The team partners closely with commercial and functional leaders to address critical business questions, develop data-driven recommendations, and build solutions that can scale globally. The Data Scientist will lead GDS&AA projects across the Analytics Continuum by conceptualizing, developing, and deploying machine learning, predictive modeling, simulation, and optimization solutions tied to high value priority use cases and tracked value delivery. This role spans a broad portfolio across Supply Chain including Procurement, Manufacturing, NetOps, Customer Service and Logistics and Planning, and requires strong stakeholder management to independently drive projects from scoping through execution and adoption.

Requirements

BE/BTech (Computer Science or Information Technology preferred) and/or MBA/PGDM in Business Analytics/Data Science, or MSc/MStat in Economics/Statistics or related fields.
4+ years of experience building statistical/ML models and translating outputs into actionable business insights and impact.
Hands-on experience with modeling techniques such as linear regression, ridge/lasso, logistic regression, random forest, gradient boosting, SVM, K-Means, hierarchical clustering, and Bayesian regression.
Strong coding skills in Python (mandatory) and SQL.
Hands-on experience applying Artificial Intelligence and Generative AI, including integrating LLMs into analytics workflows for insight generation, unstructured data analysis, feature engineering, and decision support.
Adept at using agentic coding platforms to develop rapidly (e.g., Cursor, Antigravity or similar)
Experience using GitHub and Airflow for development workflows and deployments.
Familiarity with visualization frameworks such as PyDash, Flask, and Plotly (or equivalent).
Strong understanding of cloud platforms such as Google Cloud and Snowflake, including services like Kubernetes, Cloud Build, and Cloud Run.
Proven experience working directly with business stakeholders in a client-facing or business-partnering role in a dynamic environment.

Nice To Haves

Familiarity with Supply Chain processes across Demand and Supply
Understanding of Supply Chain specific datasets and their impact on processes
Knowledge of the CPG industry and typical metrics & KPIs
Strong understanding of the advantages/limitations of ML methods in real business settings
Practical experience implementing Optimization algorithms to solve a business need
Practical experience implementing Simulation algorithms such as simpy
Deeper hands-on experience with GCP products (BigQuery, Looker/Data Studio, Kubernetes, Cloud Build/Run)
Experience operationalizing models in cloud environments using Airflow + Docker end-to-end
Knowledge and experience in UI/UX design specifically as it relates to visualising advanced analytics outputs

Responsibilities

Conceptualize and build predictive models, simulations, and optimization solutions to answer business questions and enable decision-making.
Apply ML/AI techniques to develop inferential and predictive models that can be scaled and reused across supply functions.
Deliver end-to-end analytics solutions including data extraction, data preparation, feature engineering, modeling, validation, and business storytelling.
Validate models and continuously improve algorithms, performance, stability, and business relevance over time.
Deploy and operationalize models on ML platforms using Airflow + Docker on GCP
Analyze large datasets to identify trends, patterns, and commercial opportunities using BigQuery, SQL, and enterprise data assets.
Present insights in a clear, business-friendly way through executive-ready narratives and recommendations.
Prototype full-stack tools and apps using agentic coding platforms and industry standard libraries like PyDash, Flask, Plotly, Streamlit, React.JS etc
Partner closely with supply chain teams across divisions and collaborate effectively in a global, cross-functional environment.