2 jobs for "Applied Data Scientist - Operations Decision Intelligence"

Applied Data Scientist - Operations Decision Intelligence

At Apple - Seattle

Posted on Oct 15

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Lead Data Scientist

At Nike - Beaverton

Posted on Nov 4

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Apple

Applied Data Scientist - Operations Decision Intelligence

Seattle, WA$137,500 – $207,100Posted 23 days ago

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Apple Services Engineering (ASE) powers the AI and LLM features behind experiences that hundreds of millions of users love every day. As these systems increasingly rely on human-in-the-loop evaluation, the quality of our products is directly constrained by the speed of our evaluation processes. We believe that to build exceptional AI, you need exceptional evaluation operation tools.

Apple Services Engineering (ASE) powers the AI and LLM features behind experiences that hundreds of millions of users love every day. As these systems increasingly rely on human-in-the-loop evaluation, the quality of our models is directly constrained by how fast, accurately, and systematically our operations can scale. We believe that to build exceptional AI, you need exceptional operational intelligence. In this role, you will own development of the data systems, predictive models, and self-service automation tools that optimize workforce capacity, forecast volatile demand, and transform evaluation operations into an agile, AI-driven platform.

Description

The ML Data Quality Operations team within Human-Centered AI is looking for an Applied Data Scientist to take technical ownership of our core Operations Intelligence and Decision Support stack. In this role, you will design, scale, and evolve the systems that drive systematic workforce planning, predictive demand forecasting, spend optimization, and real-time operational telemetry across our human-in-the-loop pipelines.

You will bridge applied quantitative modeling, data engineering, and intelligent automation-developing algorithmic forecasting models that absorb demand volatility and building conversational, tool-driven workflows that enable self-service operational decision-making. Your work will eliminate operational friction, turn complex resource and capacity constraints into automated decisions, and directly expand the throughput of Apple's features evaluation workflows. This role demands a pragmatic builder with fluency across data systems and applied modeling: you will prototype, validate, and ship practical, scalable tooling that empowers operations leads and engineering partners across Apple.","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 that serve as the single source of truth across human-in-the-loop workflows and vendor execution.

Develop practical, scalable decision-support tooling and simulation capabilities that allow operations leads to evaluate trade-offs, model capacity constraints, and optimize spend in real time.

Build and evolve intelligent, conversational automation and tool-calling workflows that streamline operational inquiries and turn manual triage into self-service actions.

Establish monitoring and anomaly detection systems across operational metrics to proactively identify pipeline bottlenecks, SLA risks, and spend variances before they impact delivery.

Partner closely with downstream users of these systems-operations leads, evaluation engineers, and program managers-to ground tooling design in real feedback, daily workflows, and evolving feature needs.

Communicate analytical findings, capacity forecasts, and tooling roadmaps clearly to both technical and operational stakeholders.

Preferred Qualifications

Experience supporting Data Operations, Human-in-the-Loop (HITL) annotation pipelines, or AI/ML features evaluation workflows.

Experience designing internal tools, services, or interfaces (e.g., lightweight web frameworks like FastAPI, Streamlit, or similar) that are intuitive, configurable, and extensible by practitioners who did not build them.

Familiarity with workflow orchestrators (e.g., Airflow or similar engines) and containerized deployment patterns.

Demonstrated passion for leveraging AI, automation, and decision intelligence to eliminate manual operational drag and scale organizational efficiency.

Minimum Qualifications

3-5+ years of industry experience in applied science, data engineering, or operations research, with demonstrated experience building practical data systems or predictive models.

Strong programming proficiency in Python and SQL, with hands-on experience designing, deploying, and maintaining resilient data pipelines and backend utilities.

Experience developing quantitative or predictive models (e.g., time-series forecasting, resource allocation, capacity planning, or constrained optimization) applied to operational or business problems.

Experience building or integrating intelligent automation, conversational interfaces, or tool-calling/retrieval workflows using modern LLM APIs to automate complex processes.

Demonstrated experience translating fragmented operational data streams into unified data models, automated monitoring systems, and actionable decision tools.

Demonstrated ability to work directly with cross-functional users to incorporate feedback into tooling design, and to communicate 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.

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $137,500 and $207,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

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

About Apple

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