Sr. Analyst, Global Data Science Supply Chain

Colgate-Palmolive · All India

  • Experience4–8 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted16 Sept 2026

About Colgate-Palmolive

Colgate-Palmolive is hiring in All India in consumer goods. This role looks for around 4+ years of experience.

Skills

  • Python
  • SQL
  • Machine Learning
  • Artificial Intelligence
  • Generative AI
  • Statistical Modeling
  • Predictive Modeling
  • Linear Regression
  • Ridge Regression
  • Lasso Regression
  • Logistic Regression
  • Random Forest
  • Gradient Boosting
  • Support Vector Machines
  • K-Means Clustering
  • Hierarchical Clustering
  • Bayesian Regression
  • Google Cloud
  • Snowflake
  • Kubernetes
  • Cloud Build
  • Cloud Run
  • GitHub
  • Airflow
  • Docker

The role

A data scientist at a consumer products company develops machine learning, supply chain analytics, and optimization solutions for procurement, manufacturing, logistics, and planning, using Python, SQL, and Google Cloud. The role also operationalizes predictive models with Airflow and Docker and translates analytical outputs into business recommendations.

Full job description

Relocation Assistance Offered Within Country

Job Number #175569 - Mumbai, Maharashtra, India

Who We Are

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specialising in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!

Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core valuesCaring, Inclusive, and Courageouswe foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.

Role Summary :

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.

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 GCPAnalyze 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 etcPartner closely with supply chain teams across divisions and collaborate effectively in a global, cross-functional environment.

Required Qualifications/Experience :

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.

Preferred Qualifications/Experience :

Familiarity with Supply Chain processes across Demand and Supply Understanding of Supply Chain specific datasets and their impact on processesKnowledge of the CPG industry and typical metrics & KPIs Strong understanding of the advantages/limitations of ML methods in real business settingsPractical experience implementing Optimization algorithms to solve a business needPractical experience implementing Simulation algorithms such as simpyDeeper 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-endKnowledge and experience in UI/UX design specifically as it relates to visualising advanced analytics outputs

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