Collaborating with organizational leaders to identify informational needs. Acquiring data from primary and secondary sources. Cleaning and reorganizing data for analysis. Analyzing data sets to spot trends and patterns that can be translated into actionable insights. Combine business understanding, data processing, programming, statistical modeling, and data visualization to derive actionable insights from broad data sets Work with the Leadership Team and other stakeholders to formulate analytical questions, make relevant assumptions, build statistical models and search for signals and pattern that is relevant to the business questions Confer with the Data Team to ensure data quality is being maintained End-to-end ownership of machine learning models - training, testing, evaluating, tuning, generalizing, debugging and monitoring Continuously champion high quality data practices - from architecture, normalization, data cleansing, data usage, data aggregation, data privacy & access control, tiered storage, and documentation - essentially the entire data lifecycle Be a data evangelist to continuously grow awareness around data and promote data-driven nature in decision-making.