Clorox is looking to apply data science techniques across its portfolio of brands to develop novel tools and analyses that push the boundaries of marketing analytics, build data products, and translate data into clear and compelling insights for business impact.
Requirements
- 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.
- Skilled in data exploration, cleaning, and feature engineering.
- 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.
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 (e.g., LLMs, embeddings, RAG pipelines) for use cases like personalized marketing, customer insights, or content generation.
- Scope and define data science projects, set clear deliverables, and collaborate with stakeholders to develop and deploy impactful models.
- Write clean, well-organized code in GitHub repositories, following version control and collaboration best practices for development with other members of the team
- Collaborate closely with data engineers to ensure data quality, feature engineering, and the development of efficient data pipelines.
- Act as a strategic partner to business stakeholders, helping them frame problems in a data-driven way and translating business goals into analytical solutions.
- Present analytical findings and model results through compelling storytelling, using visualizations and business context to drive alignment and decision-making.
Other
- Hybrid role - 3 days in our of our offices in US
- Proven experience working with business stakeholders; business-facing or consulting experience is preferred.
- Ability to translate business problems into data science solutions and scope data projects with measurable impact.
- Comfortable leading discovery sessions and contributing strategically to cross-functional teams.
- Strong communication and collaboration skills; able to work with both technical and non-technical stakeholders.
