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Applied Data Scientist - Operations Decision Intelligence

Apple Seattle, WA

Seattle, WA

Today

$138k - $207k/yr Full time Anomaly Detection Artificial Intelligence Capacity Planning

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Job Description

Applied Data Scientist role in Apple Services Engineering (ASE) focused on owning an Operations Intelligence and Decision Support stack.

Responsibilities

Design and implement predictive forecasting and capacity allocation models to project evaluation demand, workforce utilization, and budget trajectories under high volatility.
Build, automate, and maintain resilient data pipelines and operational telemetry used as a single source of truth across human-in-the-loop workflows and vendor execution.
Develop decision-support tooling and simulation capabilities that help operations leads evaluate trade-offs, model capacity constraints, and optimize spend in real time.
Create and evolve intelligent conversational automation and tool-calling workflows to streamline operational inquiries and convert manual triage into self-service actions.
Establish monitoring and anomaly detection across operational metrics to identify pipeline bottlenecks, SLA risks, and spend variances before they impact delivery.
Work closely with downstream users, including operations leads, evaluation engineers, and program managers, to align tooling with real feedback and daily workflows.
Communicate analytical findings, capacity forecasts, and tooling roadmaps to technical and operational stakeholders.

Requirements

Experience supporting Data Operations, Human-in-the-Loop (HITL) annotation pipelines, or AI/ML features evaluation workflows.
Experience designing internal tools, services, or interfaces using lightweight web frameworks (example frameworks include FastAPI, Streamlit, or similar) that are intuitive and extensible for practitioners.
Familiarity with workflow orchestrators (example: Airflow or similar) and containerized deployment patterns.
Demonstrated passion for applying AI, automation, and decision intelligence to reduce manual operational drag and improve organizational efficiency.
3-5+ years of industry experience in applied science, data engineering, or operations research, including building practical data systems or predictive models.
Strong Python and SQL programming skills, with hands-on experience building and maintaining resilient data pipelines and backend utilities.
Experience developing quantitative or predictive models for operational or business problems (examples include time-series forecasting, resource allocation, capacity planning, or constrained optimization).
Experience building or integrating intelligent automation, conversational interfaces, or tool-calling/retrieval workflows using modern LLM APIs to automate complex processes.
Demonstrated ability to translate fragmented operational data streams into unified data models, automated monitoring systems, and actionable decision tools.
Ability to partner directly with cross-functional users to incorporate feedback into tooling design and explain technical concepts clearly to non-technical partners.
MS or PhD in Computer Science, Data Science, Operations Research, Statistics, or a related quantitative field, or equivalent practical experience.

Technology

Python
SQL
FastAPI
Streamlit
Airflow
LLM APIs

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition for formal education related to advancing career
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligible for discretionary restricted stock unit awards
Ability to purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan
May be eligible for discretionary bonuses or commission payments, as well as relocation

Role Description

The ML Data Quality Operations team within Human-Centered AI is looking for an Applied Data Scientist to take technical ownership of core Operations Intelligence and Decision Support systems.

Design, scale, and evolve systems for workforce planning, predictive demand forecasting, spend optimization, and real-time operational telemetry across human-in-the-loop pipelines.
Bridge applied quantitative modeling and data engineering by building forecasting models that absorb demand volatility and conversational, tool-driven workflows for self-service operational decision-making.
Reduce operational friction by automating decisions from complex resource and capacity constraints, improving throughput for Apple’s features evaluation workflows.
Prototype, validate, and ship practical, scalable tooling that enables operations leads and engineering partners.

Location: Seattle, WA (onsite)

Compensation: USD 137,500 - 207,100 per year (base pay depends on skills, qualifications, experience, and location)

Note: Apple benefits, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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