Head of Data Science at TikTok

| Greater LA Area
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Responsibilities

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy by offering a home for creative expression and an experience that is genuine, joyful, and positive.

Responsibilities: - Build and manage high performance, responsive teams of data scientists and analysts that are able to not only keep up with but also pioneer in this space - Develop goal metrics and evaluate team performance - Analyze data trends to identify opportunities and drive product strategy - Lead in data-informed decision-making throughout the org and broader company - Synthesize analytics and statistical approaches into easy-to-consume storylines, both visually and verbally, and provide indicated actions for executive audiences - Regularly report findings to key executive stakeholders across the company - Collaborate with and influence leadership to ensure Data Science directly impacts strategy - Drive an organizational effort toward better understanding user needs and pain points, and propose solutions that data science can provide to further this goal - Oversee the building/maintaining of reports, dashboards, and metrics to monitor the performance of our products - Develop deep partnerships with engineering and product teams to deliver on major cross-functional measurements, testing, and modeling efforts - Develop new techniques and data that will enable answering previously unanswerable and new questions - Ensure our data and analysis are reliable and rigorous - Partner with Data Engineering to ensure the right metrics are created and validate accuracy - Ensure actionable measurement plans by developing goal metrics and evaluating performance - Investigate ad hoc issues and debugging regressions - Determine ways to use data as a strategic asset in - Validate metric accuracy for internal and external reporting - Generate useful features from large amounts of data - Drive team to analyze creatives and surface insights that will help drive engagement and retention - Apply supervised and unsupervised machine learning techniques, such as linear and logistic regression, decision trees, and k-means clustering - Develop segmentation models, classification models, propensity models, LTV models, experimental design, optimization models - Perform statistical analysis such as KPI deep dives, performance marketing efficiency, behavioral clustering, and user journey analytics - Curate audiences and inform engagement tactics to enable differentiated, relevant marketing touches across channels (social, email, in app, push)

Qualifications

Minimum Qualifications: - BS/BA in a quantitative field such as Computer Science, Engineering, Math, Statistics or equivalent years of experience - 10+ years of experience in data science, algorithmic engineering, or machine learning - 5+ years of experience in managing and mentoring data science, data engineering, and analytics teams in a technology company - 7+ years of experience doing quantitative analysis including experience with SQL or other programming languages (Python, R, etc.) - Experience designing a data science roadmap and executing the vision behind it - Experience building data science models (Regression, Decision Trees, K-Means, etc.) - Experience with large data sets and analytical tools, e.g. Hive, Spark - Experience communicating the results of analysis to an executive audience - Experience working with international partners in different time zones - Experience instilling a culture of ownership, collaboration, and results. - Track record of recruiting talent in analytics, data science, and software engineering. - Track record of delivering data-driven products and insights, and influencing product and engineering decisions. Preferred Qualifications: - 15+ years’ experience in algorithmic engineering, data science, or machine learning - MS or PhD in a quantitative field such as Computer Science, Engineering, Math, Statistics, etc.

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