As a Data Scientist in Marketing, you will have the opportunity to apply data science techniques across our portfolio of brands to develop novel tools and analyses that push the boundaries of marketing analytics within the company
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
Lead discovery sessions with marketing, product, and leadership teams to understand pain points and identify opportunities where data science can create value
Present analytical findings and model results through compelling storytelling, using visualizations and business context to drive alignment and decision-making
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
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
Ability to translate business problems into data science solutions and scope data projects with measurable impact
Benefits
robust health plans
a market-leading 401(k) program with a company match
flexible time off benefits (including half-day summer Fridays depending on location)
inclusive fertility/adoption benefits
comprehensive, competitive benefits that prioritize all aspects of wellbeing and provide flexibility for our teammates’ unique needs
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