Latin America AIML Data Scientist (Decision Intelligence)

Imagine what you could do here. The people here at Apple don’t just create
products — they create the kind of wonder that’s revolutionized entire
industries. It’s the diversity of those people and their ideas that inspires the
innovation that runs through everything we do, from amazing technology to
industry-leading environmental efforts. Join Apple, and help us leave the world
better than we found it! Apple's ALAC 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 an ALAC DI Data Scientist, 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, and more. This role will
operate in both capacities — augmenting existing data solutions as well as
innovating and trailblazing data science projects, crafting analytic experiences
that simplify data into insights and catalyze decision-making. Analytics is a
team sport and in your role, you will be key in leading and influencing teams on
the translation of business problems and questions into data science models.


DESCRIPTION


Insight Pipeline & ML Development - Build and scale the automated insight
pipeline that powers the ALAC sales organization — developing ML models that
detect opportunities, diagnose performance issues, and recommend actions - 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 GENAI & Agent Integration - Embed insights into AI
agents, dashboards, and GenAI-powered tools used by sales teams - Build RCA and
recommendation engines that enhance summarization and chatbot capabilities -
Analyze agent interactions and implement LLM evaluation pipelines to measure
factual accuracy, latency, and user satisfaction Experimentation & Scaling -
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 - Influence upstream data model design, drive KPI definitions, and develop
your own data solutions as needed Translation & Stakeholder Partnership - Act as
a data translator, bridging the gap in expertise between technical teams — data
analysts, data engineers, software developers — and business stakeholders, with
the ability to speak the language of both


MINIMUM QUALIFICATIONS


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


PREFERRED QUALIFICATIONS


Production experience with GenAI frameworks (LangChain, LlamaIndex, Haystack,
etc.) Familiarity with LLM observability and evaluation tools (LangSmith,
Weights & Biases, TruLens, etc.) Experience with vector databases, embedding
models, and retrieval algorithms Knowledge of agent architectures and knowledge
graphs for LLM applications Experience with CI/CD pipelines and MLOps practices
Experience with drift detection and model monitoring in production Track record
of presenting insights to senior leadership and influencing business strategy
Sound 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 leadership Advanced Degree (MS or Ph.D.) in Economics,
Electrical Engineering, Statistics, Data Science, or a similar quantitative
field Spanish proficiency