Senior Data Scientist, Global Data Science
About The Position
The Global Data Science & Advanced Analytics function at Colgate-Palmolive partners with businesses to solve high-impact problems through advanced analytics, delivering measurable value and scalable solutions across markets. The Senior Data Scientist, Global Professional Marketing Analytics is an Individual Contributor role responsible for building and scaling advanced analytics capabilities to measure and optimize Professional Marketing effectiveness across Oral Health, Pet Health (Hill’s), and Skin Health. This role focuses on creating net-new global analytics solutions, connecting disparate professional data sources, and embedding analytics into commercial decision-making. As a Senior Data Scientist, this role leads end-to-end analytics solutioning—from problem framing and data strategy through modeling, validation, and storytelling—while independently managing senior stakeholders across Marketing, Sales, Finance, IT, and Data Science.
Requirements
- Bachelor’s degree in Economics, Statistics, Data Science, Engineering, Business Analytics, or related quantitative fields
- 4–6 years of experience in Data Science, Advanced Analytics, Marketing Analytics
- Strong, hands-on expertise in Python (mandatory) and SQL
- Deep understanding and hands-on experience in statistical modeling, predictive analytics, forecasting, simulation, and optimization
- Experience developing statistical and machine learning models including linear and logistic regression (linear, ridge, lasso), random forest, SVM, gradient boosting, K-Means clustering, hierarchical clustering, and Bayesian regression
- Hands-on experience applying AI and machine learning techniques, including the use of Generative AI and Large Language Models (LLMs) for insight generation, automation, and advanced analytics use cases
- Experience integrating LLMs and GenAI solutions into analytics workflows (e.g., feature engineering, insight summarization, decision support, or unstructured data analysis)
- Knowledge of model deployment tools and MLOps practices, including GitHub and Airflow
- Understanding of data visualization frameworks such as PyDash, Flask, and Plotly
- Strong understanding of cloud platforms and data infrastructure, including Google Cloud and Snowflake
- Familiarity with containerization and orchestration services such as Kubernetes, Cloud Build, and Cloud Run
- Ability to independently manage senior global stakeholders and translate analytics into actionable insights
Nice To Haves
- Experience in Consumer Health, Pharma, or Professional-centric FMCG analytics roles
- Strong understanding of Professional Marketing and advocacy journeys
- Experience building global analytics capabilities or standardized toolkits
Responsibilities
- Lead complex, end-to-end advanced analytics initiatives as an Individual Contributor, owning solution architecture, modeling approach, and execution
- Personally design and implement core modeling components in Python and SQL while setting technical direction for scalable analytics solutions
- Build and evolve predictive models, simulations, forecasting, and optimization frameworks that become reusable global assets
- Apply AI, GenAI, and LLMs to professional marketing analytics, shaping how these technologies are operationalized across use cases
- Drive hands-on experimentation with LLMs for insight generation, unstructured data analysis, automation, and decision-support systems
- Architect and maintain a Global Professional Marketing Analytics Toolkit , ensuring scalability, robustness, and long-term sustainability
- Define and operationalize measurement, ROI frameworks, and analytical standards adopted across markets
- Lead cross-market meta-learnings and synthesize insights that influence category and global strategy
- Translate complex analytics and AI outputs into executive decision frameworks and strategic recommendations
- Partner deeply with Marketing, Sales, Finance, IT, and Data Science to embed analytics into core commercial processes
- Act as a technical thought leader within Global Data Science, influencing best practices, tooling, and methodologies
- Ensure solutions align with enterprise data governance and responsible AI principles
- Accelerate adoption of analytics and AI solutions by coaching stakeholders, setting standards, and demonstrating value at scale
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
