Senior Data Scientist

About usThe Data & Technology Team within the Strategy & Innovation Office will leverage technology and data to help our business create and innovate. We are looking for a data science leader who is obsessed about bridging between data and decision-making. This role will be responsible for the build, scale and shape the direction of our business through data science & analytics. The ideal candidate is "full-stack" data powerhouse who uses data to guide decision making to ensure the best experiences. This role will report to the Data Scientist Manager . 1. 6 Month Expectations Support Technology and Product Management team in mapping out the data vision and future state data pipeline and architecture Translate business questions and concerns into specific analytical questions that can be answered with available data using statistical and machine learning methods Provide feedback to our science and engineering teams on the applicability of technical solutions from the business perspective Solve real-world problems by getting and analyzing large amounts of data, diving deep to identify business insights and opportunities, designing simulations and experiments, developing statistical and ML models tailored to business needs, and collaborating with Scientists, Engineers, BIEs, and Product Team. Develop statistical and analytic models to uncover insights and segmentations that drive the business forward and uncover new areas of opportunities Apply machine learning methodologies by developing new sources, developing and testing enhancements, running computational experiments, and fine-tuning parameters for new ones Write code (Python, Scala, SQL, etc.) to obtain, manipulate, and analyze data 2. 12+ Month Expectations Build decision-making models and propose solutions for the business problem you define Formalize assumptions about how our systems are expected to work, create statistical definition of the outlier, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions are needed. Given anecdotes about anomalies or using automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes Drive implementation forward while enabling the business scaling vectors Develop scalable data pipelines to support analytics needs Communicate verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations Build and lead a team of data scientists and analysts to develop AI, ML and other algorithmic solutions to automate tasks and generate insights