17 Media has become a leading LiveStreaming platform that connects talents and viewers from over the world. 17 Media’s Data Science & Analytics team sits at the heart of the place. The team not only build the data warehouse but also provide insights to direct the company’s business units to optimize streamers and payers efficiency and liquidity. The team also produces quantitative analysis that enables the product to run A/B test experiments for product and business strategies that yield an efficient and competitive platform.
We’re seeking a proven Sr. Data Science and Analytics Director excited about data architect, statistical modeling, forecasting, analytics, experimentation, and mining user behavior data to work on challenges. You and your team will collect data and produce quantitative insights to shape competitive strategies.
As a leader, you will set best practices, architect solutions, design processes and build a team that will grow at a fast clip. You’ll partner with engineering and product executives to design strategy and vision.
You will be highly considered if you have the following experience: Working knowledge of Data Warehouse and SQL. Experience designing and deploying high-performance systems with reliable ETL, monitoring and event tracking practices Demonstrated ability to analyze large data sets to identify gaps and inconsistencies, provide data insights, and advance effective product solutions Excellent communication skills, both written and verbal 3+ years management experience 5+ years of relevant experience, ideally a mix of management consulting, business operations, and start-up company experience. Bachelor’s and/or Master’s degree, preferably in CS, or equivalent experience And it will be great if you are equipped with the following skills: Fluency in the core toolkit of Data Engineering/Science: GCP : BigQuery/Dataflow/Firebase/DataStudio Open Source : Embulk/Digdag/Airflow Manipulating large-scale data sets Implementing visualizations, dashboards, and reports Descriptive and predictive modeling