Data Scientist, US Decision Intelligence
Apple · Cupertino ·
- Category
- Data science
- Experience
- 4+ years
Apple · Cupertino ·
Clarios · Mexico, Nuevo León, San Pedro Garza Garcia
Kstack · São Paulo, SP, BR
NewRocket · USA - Remote
NewRocket · USA - Remote Eastern US
Data scientist on Apple's US Decision Intelligence team, building and scaling the automated insight pipeline for Apple's sales organization. Develops ML models for forecasting, anomaly detection, and recommendations, and embeds insights into AI agents, dashboards, and GenAI tools using Python, SQL, cloud data platforms, and LLM/RAG techniques.
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 there's no telling what you could accomplish.
Apple’s 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 customers.
Apple's 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 customers.
As 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, etc. This 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. You'll develop ML models that detect opportunities, diagnose performance issues, and recommend actions—then embed these insights into AI agents, dashboards, and GenAI-powered tools used by sales teams.
Your core responsibilities include:
Lead end-to-end insight development: from data preparation and statistical analysis to LLM prompt engineering that translates findings into sales-ready insights.
Design and deploy ML models for forecasting, anomaly detection, attribution modeling, and causal inference—either building custom solutions or adapting Apple's existing ML services.
Build RCA and recommendation engines that enhance summarization and chatbot capabilities. Analyze agent interactions and implementing LLM evaluation pipelines to measure factual accuracy, latency, and user satisfaction.
Support experimentation and A/B testing for new insight types and interaction methods.
Partner with AI engineers and PMs to scale features across regions and tools.
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 both.
Influence upstream data model design, drive KPI definitions, and develop your own data solutions as needed.
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