> Markdown version of [/jobs/ext/1958176-data-scientist-platform-infrastructure](https://www.wearedevelopers.com/jobs/ext/1958176-data-scientist-platform-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - Platform Infrastructure - **Company:** Tiktok Inc. - **Location:** Los Angeles, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** A/B Testing, Data as a Services, Data Infrastructure, Extract Transform Load (ETL), Hadoop Distributed File System, Human-Computer Interaction, Statistical Hypothesis Testing, Python (Programming Language), SQL Databases, Apache Yarn, Core Data, Data Management, Data Pipelines, User Identification - **Published:** August 6, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/data-scientist-platform-infrastructure-los-angeles-ca-usa-58818287 ## About the Role tracking, identity resolution, URL parameter frameworks * Oversee data infrastructure governance and resource management (e.g., HDFS/YARN queues, efficient resource allocation) * Ensure data quality, reliability, and governance with validation and monitoring for pipelines and datasets * Build and maintain internal data tools, dashboards, and data services to improve efficiency and cross-functional alignment * Collaborate with marketing, product, research, and engineering to align data definitions and platform capabilities Tasks * Master's degree in a quantitative discipline * 3+ years in data science roles within business strategy, marketing, finance, engineering, or analytics * Strong expertise in hypothesis testing and A/B testing methodologies * Proficiency in SQL and Python or R for analysis and pipelines * Experience designing, maintaining, and optimizing reporting dashboards and data pipelines * Experience translating data findings for non-technical stakeholders into strategic aaaa measurement Key requirements * ## Description Experteer Overview You will advance the Global Brand Data Science team's mission to boost marketing efficiency and impact through scalable data platforms, robust measurement, and actionable insights. You'll work with cross-functional partners to design and operationalize data assets, support global campaigns, and enable self-serve analytics. This role focuses on building data infrastructure, reliable pipelines, and governance to connect marketing touchpoints with outcomes. It's an opportunity to shape measurement at scale and influence strategic decisions across the organization. Compensation / Benefits * Scale and maintain a unified data infrastructure to support global campaign experimentation and measurement * Design, build, and manage end-to-end ETL pipelines transforming ads, creative, and user interaction data into analysis-ready datasets * Develop core data models and analytical schemas including standardized tables and derived metrics * Establish tracking foundations: exposure tracking, identity resolution, URL parameter frameworks * Oversee data infrastructure governance and resource management (e.g., HDFS/YARN queues, efficient resource allocation) * Ensure data quality, reliability, and governance with validation and monitoring for pipelines and datasets * Build and maintain internal data tools, dashboards, and data services to improve efficiency and cross-functional alignment * Collaborate with marketing, product, research, and engineering to align data definitions and platform capabilities Tasks * Master's degree in a quantitative discipline * 3+ years in data science roles within business strategy, marketing, finance, engineering, or analytics * Strong expertise in hypothesis testing and A/B testing methodologies * Proficiency in SQL and Python or R for analysis and pipelines * Experience designing, maintaining, and optimizing reporting dashboards and data pipelines * Experience translating data findings for non-technical stakeholders into strategic recommendations Key requirements * ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [Product Innovation through Partnerships - Search and Local Services](https://www.wearedevelopers.com/videos/100020-product-innovation-through-partnerships-search-and-local-services) - [Beyond Autocomplete: Local AI Code Completion Demystified](https://www.wearedevelopers.com/videos/961-beyond-autocomplete-local-ai-code-completion-demystified) ## Related Articles - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 137 - AI'm not sure about this](https://www.wearedevelopers.com/magazine/485-dev-digest-137-ai-m-not-sure-about-this) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)