Lead Data Scientist building GenAI - driven products and ML solutions for S&P Global. Mentoring team members and delivering high - impact projects in a global environment.
About the role
- Data Scientist at Clorox developing and deploying AI/ML models. Collaborating with cross-functional teams to derive insights and drive business impact in marketing.
Responsibilities
- Contribute to the development and deployment of end-to-end AI/ML/Gen AI models, focusing on marketing, measurement, and predictive analytics
- Explore, test and implement GenAI solutions for use cases like personalized marketing, customer insights, or content generation
- Scope and define data science projects, set clear deliverables, and collaborate with stakeholders
- Write clean, well-organized code in GitHub repositories, following version control and collaboration best practices
- Collaborate closely with data engineers to ensure data quality, feature engineering, and development of data pipelines
- Act as a strategic partner to business stakeholders, helping them frame problems and find analytical solutions
- Lead discovery sessions with marketing, product, and leadership teams to understand pain points and identify data science opportunities
- Present analytical findings and model results through visual storytelling
Requirements
- Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field
- CPG experience is preferred
- 1+ years of relevant experience with a Master's degree, or 2–3+ years of experience with a Bachelor's degree
- Proven experience working with business stakeholders; business-facing or consulting experience is preferred
- Proficiency in Python and SQL
- Experience developing and deploying machine learning and generative AI (e.g., LLMs, embeddings, RAG pipelines) models
- Skilled in predictive modeling, personalized marketing, or customer analytics use cases
- Comfortable working with unstructured/messy data
- Familiarity with GitHub and collaborative version control best practices
- Experience with cloud platforms such as Google Cloud (BigQuery, GCS) or Azure Synapse is a plus
- Knowledge of Docker and cloud-based deployment is an advantage
Benefits
- Robust health plans
- 401(k) program with a company match
- Flexible time off benefits (including half-day summer Fridays depending on location)
- Inclusive fertility/adoption benefits
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