Data Scientist, US Decision Intelligence

Imagine what you could do here. At Apple new ideas have a way of becoming outstanding products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could Sales organization generates the revenue needed to fuel our ongoing development of products and services. This in turn enriches the lives of hundreds of millions of people around the world. We are in many ways the face of Apple to our largest US Decision Intelligence (DI) team is looking for a talented individual who is passionate about crafting implementing and operating analytical solutions that have a direct and measurable impact on Apple Sales and its a Data Scientist US Decision Intelligence you will employ predictive modeling data visualization and statistical analysis techniques to build end-to-end solutions for internal stakeholders leveraging sales performance data market data programs external data role will operate in both capacities to augment existing data solutions as well as innovate and trailblazing data science projects crafting analytic experiences that simplify data into insights and catalyze decision-making.

In this role you will build and scale the automated insight pipeline that powers our sales organization. Youll develop ML models that detect opportunities diagnose performance issues and recommend actionsthen embed these insights into AI agents dashboards and GenAI-powered tools used by sales core responsibilities include: n- Lead end-to-end insight development: from data preparation and statistical analysis to LLM prompt engineering that translates findings into sales-ready - Design and deploy ML models for forecasting anomaly detection attribution modeling and causal inferenceeither building custom solutions or adapting Apples existing ML - Build RCA and recommendation engines that enhance summarization and chatbot agent interactions and implementing LLM evaluation pipelines to measure factual accuracy latency and user - Support experimentation and A/B testing for new insight types and interaction - Partner with AI engineers and PMs to scale features across regions and - Act as a data translator bridging the gap in expertise between technical teams made up of data analysts data engineers software developers and business stakeholders. Successfully bridging analytics and business with the ability to speak the language of - Influence upstream data model design drive KPI definitions and develop your own data solutions as needed.

4 years of experience in a Data Science Data Analysis or Data Visualization -on experience with LLMs RAG architectures and prompt proficiency in Python and ML/data science knowledge of statistical data analysis predictive modeling classification Time Series techniques sampling methods multivariate analysis hypothesis testing and drift in SQL and experience with cloud data platforms (Snowflake Spark BigQuery etc.)nExpertise with data visualization tools (such as Tableau d3 plotly etc.) for data analysis and presentation. Experience with Tableau Server TabPy and Extensions is a with Git and collaborative development with deployment frameworks and tools (Docker Kubernetes FastAPI or similar).nComfort with ambiguity. Ability to structure complex analysis through data analysis and strategy ability to translate business problems into technical solutions and communicate findings to non-technical co-developing with data scientists and software engineers in production time management skills with the ability to collaborate across multiple to balance competing priorities long-term projects and ad hoc degree in Computer Science Statistics Mathematics Engineering Economics Applied Mathematics Machine Learning or a related field.

Production experience with GenAI frameworks (LangChain LlamaIndex Haystack etc.)nFamiliarity with LLM observability and evaluation tools (LangSmith Weights u0026 Biases TruLens etc.)nExperience with vector databases embedding models and retrieval algorithmsnKnowledge of agent architectures and knowledge graphs for LLM applicationsnExperience with CI/CD pipelines and MLOps practicesnExperience with drift detection and model monitoring in productionnTrack record of presenting insights to senior leadership and influencing business strategynSound communication skills - adept at messaging domain and technical content at a level appropriate for the audience. Strong ability to gain trust with stakeholders and senior Degree (MS or Ph.D.) in Economics Electrical Engineering Statistics Data Science or a similar quantitative field.