{"id":1236581,"url":"https://alion.io/job/tiktok-data-scientist-transparency-observability-trust-and-safety","title":"Data Scientist, Transparency & Observability - Trust and Safety","company":{"id":47,"name":"TikTok","domain":"tiktok.com","url":"https://alion.io/company/tiktok","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Feishu","truth_index":{"grade":"B","score":83,"open_postings":3432,"ghost_share":0.198,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":98,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":190000,"max_usd":359000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":1343},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Anomaly Detection","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false}],"status":"live","first_seen_at":"2026-09-16T19:55:12Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-10-30T15:27:02Z","board_verified":true,"closed_at":null,"days_open":43,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":42},"description":"岗位职责 / Responsibilities\nTikTok's Trust & Safety team works to create a safe and trusted platform for billions of people around the world. We combine policy, technology, and operations to detect harmful content, protect users, and promote healthy online communities.\nThe Transparency & Observability Data Science team builds the data, metrics, and analytical capabilities that help us understand how our enforcement systems perform. Our work supports both internal decision-making and external transparency reporting, while improving the reliability, explainability, and quality of Trust & Safety data.\nAs a Data Scientist on this team, you will develop scalable metrics, monitoring systems, and analytical solutions that provide greater visibility into platform safety and help drive continuous improvements.\nResponsibilities:\n- Build Trust & Safety Metrics & Monitoring:\n- Design and develop metrics that measure Trust & Safety enforcement across different products and content types. \n- Build dashboards and monitoring solutions that provide actionable insights into platform safety. \n- Develop automated anomaly detection and alerting to identify data or operational issues early. \n- Improve Data Quality:\n- Help ensure Trust & Safety data is accurate, reliable, and delivered on time. \n- Investigate data issues, identify root causes, and improve data quality processes. \n- Partner with engineering teams to strengthen data reliability and governance. \n- Partner Across Teams:\n- Work closely with Product, Engineering, Policy, Operations, and Data teams to build trusted measurement frameworks. \n- Help create consistent and scalable approaches to transparency reporting and observability. \n- Explore AI-powered solutions for monitoring model performance and understanding their impact on platform safety. \n- Drive Business Impact:\n- Turn complex data into clear insights that support strategic decisions. \n- Identify emerging risks and opportunities through data analysis. \n- Contribute to the long-term roadmap for Trust & Safety observability and measurement.\n任职要求 / Requirements\nMinimum Qualification(s):\n- 5+ years of experience in Data Science, Data Analytics, Data Engineering, or a related quantitative field. \n- Strong SQL skills and experience working with large-scale data platforms (e.g. Hive, Spark). \n- Proficiency in Python or R. \n- Experience building data quality monitoring, reporting, or observability solutions. \n- Experience designing metrics and developing dashboards or reporting tools. \n- Strong analytical and problem-solving skills with the ability to communicate technical concepts clearly. \n- Bachelor's degree or above in a quantitative discipline such as Statistics, Computer Science, Mathematics, Engineering, or Economics. \nPreferred Qualification(s):\n- Experience in Trust & Safety, content moderation, risk management, or regulatory reporting. \n- Experience building end-to-end monitoring or observability platforms. \n- Familiarity with transparency reporting requirements such as DSA or other regulatory frameworks. \n- Experience with anomaly detection, experimentation, causal inference, or time-series analysis. \n- Experience driving data quality initiatives at scale. \n- Experience working with global cross-functional teams. \n- Passion for using data to improve online 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