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The role is responsible for leading the use of data to build predictive models and make decisions. This role must interpret and understand the Allstate Roadside Services business problems, analyze data requirements, recommend & build appropriate predictive models , coordinate and execute the projects, and communicate and share the business insights and actions recommend. Assess data and problems across departments to drive improved business results through designing, building, and partnering to implement models. Perform Data exploration, hypothesis creation, testing algorithms, scaling to large data-sets and validating results that deliver powerful insights into our data that can be used as a competitive advantage in our Network Operations, Call Centers, Claims, and more
Build best-in-class predictive models and decision tools to address Allstate Roadside Services business needs by leveraging state-of-the-art machine learning and statistical algorithms
Identify new areas of data, research and build predictive models to improve Network Operations
Work on data and problems across ARS departments to drive improved business results through designing, building, and partnering to implement models
Manage data and data requests to improve the accuracy of our data and decisions made from data analysis
Use and learn a wide variety of tools and languages to achieve results (e.g., Business Objects, Tableau, R, Python, Hadoop, Oracle)
Use best practices to develop statistical, machine learning techniques to build models that address business needs
Develop frameworks/prototypes that integrate data and machine learning/predictive modeling to make business
Effectively understand the business problems and requirements to identify the optimal modeling approach
Communicate findings to ensure models are well understood and incorporated into business processes
Utilize effective project planning techniques to break down complex projects into tasks, manage scope of projects, and ensure deadlines are kept
Work with stakeholders to ensure the project will meet their needs
Identify and develop data sources to solve business problems
Manage various analytical and modeling projects with small number of team members
Influence business partners and senior leadership on the effectiveness of machine learning/predictive modeling to solve their business problems
Maximize personal professional development to ensure continuation of a personal contribution to the team and Allstate
Master's degree or PhD preferred in a quantitative field such as statistics, mathematics, computer science, finance, or economics. Proven experience in using statistical modeling and/or machine learning techniques to build models that have driven company decision making
At least 1-3 years of predictive modeling experience or equivalent skills & ability
Must be technically proficient, mathematically agile, business savvy and good at communicating
Proven experience in managing and manipulating large, complex datasets
Working business knowledge of Roadside Services particularly Network Operations, Call Centers, and Claims
Proven experience in working with statistical software such as R, SAS. R is preferred.
Understanding of the concept of experimental design such as A/B testing and familiar with statistical hypothesis testing
Proven ability to code and develop prototypes in languages such as Python, SQL, Perl, Shell Scripts
Proven knowledge of advanced modeling technique such as classification/regression, spatial analysis, time series analysis, etc.
Experience in operation research & management using linear/integer programming is a plus
Experience in hadoop/Spark/hive is a plus
Ability to train, develop, and teach more junior modelers
Ability to learn new technologies
Ability to analyze and interpret moderate to complex concepts
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