The Data Science team at Allstate Roadside maximizes the marketplace efficiency of our services though influencing the supply and demand of rescues and rescue providers in real time. This involves developing a fundamental understanding of the rescuer behavior in a rapidly changing market, creating dynamic pricing strategies that can influence the supply of rescue providers in an area that is seeing a surge in demand. This ensures our customers enjoy the highest customer service while our rescue providers are able to maximize their earnings.This Data Scientist/Machine Learning Engineer Python role is responsible for leading the use of data to make decisions. This includes: the development and execution of new machine learning predictive modeling algorithms, the coding/development of tools that use machine learning/predictive modeling to make business decisions, searching for and integrating new data (both internal and external) that improves our modeling and machine learning results (and ultimately our decisions), and discovery of solutions to business problems that can be solved through the use of machine learning/predictive modeling.Key Responsibilities:Work on optimizing real time dispatch systems and build scalable solutions to solve challenging problems.Contribute to entire life cycle of machine learning models from ideation to deployment , monitoring and retraining.Work on variety of data sets in a cloud analytics environment, crunching millions of samples in creative ways to discover new insights and operationalize powerful solutionsCollaborate with engineering teams to design and implement software solutions for data science problems.Understand ambiguous business problems and convert them into data science solutions ie create insights, decisions, white papers and models.Develop deep understanding of the business. Research solutions to recommend strategies that impact key organization metrics. Learn quickly and adapt to changing business needQualificationsDegree in a quantitative field such as statistics, mathematics, computer science, finance.Master’s or PhD, preferred, with 2 or more years of experience.Bachelors and 5 or more years of experience.Hands-on experience in implementing, maintaining, and running machine learning models in production in Python.Experience using SQL to pull data.Experience working with ML frameworks such as SkLearn, XGBoost, and Tensorflow.Previous work doing Big Data Processing using Spark a plus.Experience designing experiments and ability to infer causal relationships a plus.Experience with operations research a plus.Ability to provide written and oral interpretation of highly specialized terms and data, and ability to present this data to others with different levels of expertise.