{"id":2510162,"url":"https://alion.io/job/apple-data-scientist","title":"Data Scientist","company":{"id":12,"name":"Apple","domain":"apple.com","url":"https://alion.io/company/apple","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Apple Jobs","truth_index":{"grade":"B","score":77,"open_postings":1008,"ghost_share":0,"stale_share":0.938,"repost_share":0,"time_to_fill_p50_days":40,"computed_at":"2026-10-14T06:34:16Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Beijing, China"],"countries":["CN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Pure Data","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SQL","optional":false},{"name":"Tool Use","optional":false},{"name":"Multi-Agent Systems","optional":true}],"status":"live","first_seen_at":"2026-10-14T06:01:52Z","employer_posted_date":"2026-10-14","last_verified_at":"2026-10-14T21:17:28Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"At Apple, we believe in hard work, a fun environment, and the creativity and innovation that come from diverse perspectives. The people here at Apple don’t just build products - they create the kind of wonder that revolutionizes entire industries. It’s the diversity of those people and their ideas that inspires the innovation running 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.\nAt Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there’s no telling what you could accomplish.\nThis is a highly visible role supporting Apple’s Sales organization in China. We are looking for a Data Scientist who can combine business understanding, analytical thinking, and applied AI capability to solve complex business problems and build scalable AI-enabled solutions.\nThis role is not a pure data science role or a pure machine learning engineering role. The ideal candidate should be able to understand ambiguous business needs, translate them into structured workflows, and design agent-based solutions that can support recurring decision-making processes. We are especially interested in candidates who have the imagination and big-picture thinking to orchestrate AI agents, manage multi-agent interactions, and turn business knowledge, data, and tools into reusable analytical products.\nDescription\nPartner closely with business stakeholders to understand priorities, identify pain points, and uncover opportunities where data and AI can improve business decision-making.\nTranslate ambiguous business questions into structured analytical frameworks, agent workflows, and scalable solution designs.\nDesign and orchestrate AI agents that can perform tasks such as business Q&A, research, information extraction, data analysis, workflow automation, and decision support.\nDefine how multiple agents interact with each other, including task decomposition, role assignment, context sharing, tool usage, memory management, validation, and final response synthesis.\nConvert recurring business processes into reusable analytics products, internal tools, or agent-based workflows.\nUse data analysis, experimentation, forecasting, causal inference, optimization, LLMs, RAG, or other applied AI techniques to diagnose business issues and support decisions.\nWork with engineering, data, product, and business teams to prototype, iterate, and productionize AI-enabled analytical solutions.\nCommunicate complex analytical and AI concepts clearly to both technical and non-technical audiences.\nHelp shape best practices for building reliable, scalable, and business-relevant AI agent solutions.\nMinimum Qualifications\nStrong quantitative, analytical, or technical background in data science, statistics, economics, operations research, computer science, engineering, or a related field; or equivalent practical experience.\nDemonstrated capability in structured problem solving, analytical thinking, and using data or AI to address business problems.\nStrong business understanding and problem-structuring ability, especially in ambiguous environments.\nProficiency in Python and SQL for data analysis, prototyping, and workflow development.\nFamiliarity with LLM applications, RAG, AI agents, tool calling, workflow automation, or applied machine learning.\nAbility to connect data and AI work to real business impact.\nStrong communication and stakeholder management skills.\nFluent verbal and written communication skills in both Mandarin Chinese and English.\nPreferred Qualifications\nPhD, or Master’s degree in Economics, Statistics, Data Science, Computer Science, Engineering, Operations Research, or a related quantitative / technical field.\nRelevant experience in data science, applied AI, analytics, product analytics, strategy, consulting, machine learning, or AI product development.\nExperience designing or building AI agents, multi-agent workflows, business copilots, research agents, Q&A agents, or automated analytical workflows.\nUnderstanding of agent orchestration concepts such as planning, routing, tool use, memory, validation, reflection, handoff, and multi-agent collaboration.\nExperience converting repeatable business needs into scalable tools, data products, or AI-enabled workflows.\nStrong product sense and imagination, with the ability to think beyond one-off analysis and design reusable solutions.\nAbility to operate with a big-picture mindset, connecting business strategy, data, AI capability, and execution feasibility.\nExperience working with engineering, product, machine learning, or data platform teams to productionize analytical or AI solutions.\nFamiliarity with experimentation, causal inference, forecasting, segmentation, optimization, or measurement strategy is a plus.\nDemonstrated business maturity, ownership, and delivered impact are valued over a fixed number of years of 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