{"id":2133660,"url":"https://alion.io/job/apple-senior-data-engineer-scientist-apple-korea","title":"Senior Data Engineer & Scientist — Apple Korea","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":81,"open_postings":969,"ghost_share":0,"stale_share":0.765,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Seoul, South Korea"],"countries":["KR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":107000,"max_usd":275000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2324},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"ETL/ELT","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false},{"name":"Snowflake","optional":true}],"status":"live","first_seen_at":"2026-06-29T08:30:49Z","employer_posted_date":"2026-10-12","last_verified_at":"2026-10-19T12:13:13Z","board_verified":true,"closed_at":null,"days_open":112,"trust":{"level":"ok","repost_count":0,"flags":[],"days_open":111},"description":"At Apple, extraordinary products begin with a deep understanding of the people who use them. Our Korea Channel Sales team leverages data to shape business strategy, optimize customer experiences, and drive growth across channels and partners.\nAs a Senior Data Engineer & Scientist, you will build the data infrastructure that connects fragmented data sources across the business - and apply that foundation to generate insights, run experiments, and develop AI-driven solutions. This dual role is ideal for someone who can architect reliable data systems and, with that same depth, design the experiments and models that turn data into business decisions.\nDescription\nIn this role, you will own the full data lifecycle - from pipeline architecture and data modeling through to statistical analysis and AI-driven insight generation. You will work closely with cross-functional teams spanning marketing, business operations, partner management, and engineering.\nEarly on, you will focus on standing up data infrastructure: building ingestion pipelines, automating dashboards, identifying data gaps, and ensuring data governance and compliance. As the foundation matures, you will shift toward data science - designing experiments, generating customer insights, and applying machine learning to optimize initiatives for sales growth.\nYou will also contribute to the development of data platforms that enable seamless collaboration with external and internal partners, and help scale analytics capabilities across the organization.\nMinimum Qualifications\n5+ years of relevant work experience in data engineering, data science, or a combined role, with hands-on depth across both disciplines\nProficiency in Python and SQL, with experience building and maintaining ETL/ELT pipelines, data models, and automated dashboards\nExperience with marketing data science methods including experimental and testing design, regression analysis, and causal inference\nSolid understanding of data governance, compliance, and access control principles\nStrong problem-structuring skills, with the ability to work through ambiguity and define clear analytical approaches\nExcellent communication and stakeholder management skills, with the ability to present to non-technical business audiences\nFluent verbal and written communication skills in both Korean and English\nPreferred Qualifications\nExperience with cloud data platforms (e.g., Snowflake)\nProficiency in machine learning methods applied to customer analytics, business optimization, or forecasting\nExperience building data-sharing platforms or partner data integration workflows\nBackground in business analytics (e.g., attribution, funnel analysis, customer lifetime value, marketing mix modeling)\nExposure to digital advertising, marketplaces, e-commerce, media, or consumer technology business related analysis\nExperience identifying repeatable business problems and converting them into scalable tools or automated workflows\nMaster’s or PhD in Computer Science, Statistics, Data Science, Economics, Operations Research, Engineering, or a related quantitative field with 5+ years of 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